1%| | 94/15290 [00:02<06:18, 40.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 99/15290 [00:02<06:18, 40.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 104/15290 [00:02<06:30, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 108/15290 [00:02<06:43, 37.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 112/15290 [00:02<06:53, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 116/15290 [00:03<08:18, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 120/15290 [00:03<07:46, 32.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 125/15290 [00:03<07:17, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 129/15290 [00:03<07:04, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 134/15290 [00:03<06:40, 37.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 138/15290 [00:03<06:49, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 142/15290 [00:03<06:54, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 146/15290 [00:03<07:08, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 150/15290 [00:04<07:00, 36.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 155/15290 [00:04<06:32, 38.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 160/15290 [00:04<06:22, 39.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 165/15290 [00:04<06:13, 40.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 170/15290 [00:04<06:12, 40.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 175/15290 [00:04<06:19, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 179/15290 [00:04<06:20, 39.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 183/15290 [00:04<06:20, 39.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%| | 187/15290 [00:04<06:23, 39.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 192/15290 [00:05<06:15, 40.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 197/15290 [00:05<06:23, 39.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 202/15290 [00:05<06:18, 39.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 206/15290 [00:05<06:26, 39.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 210/15290 [00:05<06:27, 38.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 215/15290 [00:05<06:22, 39.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 219/15290 [00:05<06:31, 38.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 224/15290 [00:05<06:26, 38.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
1%|▏ | 228/15290 [00:05<06:28, 38.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 233/15290 [00:06<06:19, 39.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 237/15290 [00:06<06:18, 39.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 241/15290 [00:06<06:25, 39.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 245/15290 [00:06<06:37, 37.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 249/15290 [00:06<06:38, 37.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 253/15290 [00:06<06:40, 37.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 257/15290 [00:06<06:46, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 261/15290 [00:06<06:40, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 265/15290 [00:06<06:37, 37.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 269/15290 [00:07<06:48, 36.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 273/15290 [00:07<06:39, 37.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 278/15290 [00:07<06:32, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 282/15290 [00:07<08:33, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 286/15290 [00:07<08:00, 31.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 290/15290 [00:07<07:33, 33.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 294/15290 [00:07<07:14, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 298/15290 [00:07<06:58, 35.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 303/15290 [00:08<06:42, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 308/15290 [00:08<06:27, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 312/15290 [00:08<06:29, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 316/15290 [00:08<06:33, 38.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 320/15290 [00:08<06:44, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 324/15290 [00:08<06:44, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 329/15290 [00:08<06:32, 38.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 333/15290 [00:08<06:32, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 337/15290 [00:08<06:35, 37.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 341/15290 [00:09<06:35, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 345/15290 [00:09<06:35, 37.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 349/15290 [00:09<06:40, 37.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 353/15290 [00:09<06:41, 37.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 357/15290 [00:09<06:40, 37.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 361/15290 [00:09<06:37, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 365/15290 [00:09<06:56, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 369/15290 [00:09<06:56, 35.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 373/15290 [00:09<06:51, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 377/15290 [00:10<06:39, 37.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
2%|▏ | 381/15290 [00:10<06:32, 37.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 385/15290 [00:10<06:28, 38.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 390/15290 [00:10<06:19, 39.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 394/15290 [00:10<06:29, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 398/15290 [00:10<07:04, 35.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 402/15290 [00:10<07:16, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 406/15290 [00:10<07:13, 34.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 410/15290 [00:10<07:14, 34.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 414/15290 [00:11<07:15, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 418/15290 [00:11<07:14, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 422/15290 [00:11<07:15, 34.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 426/15290 [00:11<06:56, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 431/15290 [00:11<06:43, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 435/15290 [00:11<06:35, 37.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 440/15290 [00:11<06:27, 38.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 445/15290 [00:11<06:18, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 449/15290 [00:11<06:20, 39.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 454/15290 [00:12<06:12, 39.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 459/15290 [00:12<06:06, 40.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 464/15290 [00:12<06:18, 39.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 468/15290 [00:12<06:23, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 472/15290 [00:12<06:20, 38.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 476/15290 [00:12<06:19, 39.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 480/15290 [00:12<06:17, 39.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 484/15290 [00:12<06:18, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 488/15290 [00:12<06:18, 39.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 492/15290 [00:13<06:20, 38.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 496/15290 [00:13<06:32, 37.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 500/15290 [00:13<06:26, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 504/15290 [00:13<06:23, 38.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 508/15290 [00:13<06:23, 38.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 512/15290 [00:13<06:19, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 516/15290 [00:13<06:31, 37.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 520/15290 [00:13<06:27, 38.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 524/15290 [00:13<07:08, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 528/15290 [00:14<06:55, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
3%|▎ | 533/15290 [00:14<06:34, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 538/15290 [00:14<06:22, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 542/15290 [00:14<06:20, 38.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 546/15290 [00:14<06:19, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 550/15290 [00:14<06:34, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 554/15290 [00:14<07:04, 34.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 558/15290 [00:14<07:13, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 562/15290 [00:14<06:54, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 566/15290 [00:15<06:54, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▎ | 571/15290 [00:15<06:36, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 576/15290 [00:15<06:22, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 580/15290 [00:15<06:57, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 584/15290 [00:15<06:57, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 588/15290 [00:15<07:05, 34.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 592/15290 [00:15<07:06, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 597/15290 [00:15<06:48, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 601/15290 [00:16<06:50, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 605/15290 [00:16<06:47, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 610/15290 [00:16<06:27, 37.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 615/15290 [00:16<06:14, 39.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 620/15290 [00:16<06:13, 39.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 624/15290 [00:16<06:16, 38.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 629/15290 [00:16<06:10, 39.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 633/15290 [00:16<06:11, 39.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 638/15290 [00:16<06:08, 39.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 642/15290 [00:17<06:11, 39.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 646/15290 [00:17<06:10, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 650/15290 [00:17<06:13, 39.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 654/15290 [00:17<06:37, 36.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 658/15290 [00:17<06:35, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 663/15290 [00:17<06:14, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 668/15290 [00:17<06:03, 40.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 673/15290 [00:17<05:57, 40.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 678/15290 [00:18<05:58, 40.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 683/15290 [00:18<06:18, 38.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
4%|▍ | 687/15290 [00:18<07:03, 34.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 692/15290 [00:18<06:44, 36.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 696/15290 [00:18<06:52, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 700/15290 [00:18<06:50, 35.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 705/15290 [00:18<06:26, 37.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 710/15290 [00:18<06:16, 38.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 714/15290 [00:19<06:18, 38.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 719/15290 [00:19<06:10, 39.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 723/15290 [00:19<06:09, 39.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 728/15290 [00:19<06:04, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 732/15290 [00:19<06:04, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 736/15290 [00:19<06:05, 39.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 740/15290 [00:19<06:09, 39.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 744/15290 [00:19<06:09, 39.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 748/15290 [00:19<06:37, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 752/15290 [00:19<06:39, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 756/15290 [00:20<06:36, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 760/15290 [00:20<06:29, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▍ | 764/15290 [00:20<06:28, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 768/15290 [00:20<06:24, 37.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 773/15290 [00:20<06:16, 38.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 777/15290 [00:20<06:21, 38.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 781/15290 [00:20<06:19, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 785/15290 [00:20<06:49, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 789/15290 [00:20<06:51, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 793/15290 [00:21<06:49, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 797/15290 [00:21<06:57, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 801/15290 [00:21<07:02, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 805/15290 [00:21<07:05, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 809/15290 [00:21<07:00, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 813/15290 [00:21<06:56, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 817/15290 [00:21<07:09, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 821/15290 [00:21<07:12, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 825/15290 [00:22<06:58, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 830/15290 [00:22<06:42, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 834/15290 [00:22<07:05, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
5%|▌ | 838/15290 [00:22<06:58, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 843/15290 [00:22<06:33, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 847/15290 [00:22<06:28, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 851/15290 [00:22<06:27, 37.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 855/15290 [00:22<06:27, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 859/15290 [00:22<06:29, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 863/15290 [00:23<06:31, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 867/15290 [00:23<06:33, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 871/15290 [00:23<06:30, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 875/15290 [00:23<06:35, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 879/15290 [00:23<06:28, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 883/15290 [00:23<06:35, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 887/15290 [00:23<06:32, 36.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 891/15290 [00:23<06:35, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 895/15290 [00:23<06:36, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 899/15290 [00:24<06:26, 37.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 903/15290 [00:24<06:27, 37.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 907/15290 [00:24<06:33, 36.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 911/15290 [00:24<06:39, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 915/15290 [00:24<06:43, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 919/15290 [00:24<06:46, 35.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 923/15290 [00:24<06:45, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 927/15290 [00:24<06:43, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 931/15290 [00:24<06:49, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 935/15290 [00:25<06:38, 36.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 939/15290 [00:25<06:41, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 943/15290 [00:25<06:31, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 947/15290 [00:25<07:32, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 951/15290 [00:25<08:04, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▌ | 955/15290 [00:25<07:43, 30.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 959/15290 [00:25<07:22, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 964/15290 [00:25<06:53, 34.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 968/15290 [00:26<06:44, 35.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 973/15290 [00:26<06:30, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 977/15290 [00:26<06:22, 37.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 981/15290 [00:26<06:20, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 985/15290 [00:26<06:40, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
6%|▋ | 989/15290 [00:26<06:37, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 994/15290 [00:26<06:19, 37.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 999/15290 [00:26<06:09, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1003/15290 [00:26<06:13, 38.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1008/15290 [00:27<06:10, 38.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1012/15290 [00:27<06:07, 38.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1016/15290 [00:27<06:07, 38.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1021/15290 [00:27<06:00, 39.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1026/15290 [00:27<05:56, 39.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1030/15290 [00:27<05:59, 39.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1034/15290 [00:27<06:04, 39.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1038/15290 [00:27<06:17, 37.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1042/15290 [00:27<06:19, 37.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1046/15290 [00:28<06:14, 38.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1051/15290 [00:28<06:04, 39.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1055/15290 [00:28<06:33, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1059/15290 [00:28<07:06, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1063/15290 [00:28<07:10, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1067/15290 [00:28<07:15, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1071/15290 [00:28<06:59, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1075/15290 [00:28<06:55, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1079/15290 [00:29<07:00, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1084/15290 [00:29<06:29, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1089/15290 [00:29<06:21, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1093/15290 [00:29<06:23, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1097/15290 [00:29<06:17, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1101/15290 [00:29<06:12, 38.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1105/15290 [00:29<06:15, 37.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1109/15290 [00:29<06:17, 37.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1113/15290 [00:29<06:13, 37.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1118/15290 [00:30<06:05, 38.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1123/15290 [00:30<05:58, 39.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1127/15290 [00:30<05:57, 39.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1132/15290 [00:30<05:49, 40.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1137/15290 [00:30<06:36, 35.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1141/15290 [00:30<06:30, 36.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
7%|▋ | 1146/15290 [00:30<06:18, 37.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1150/15290 [00:30<06:16, 37.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1154/15290 [00:31<06:12, 37.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1158/15290 [00:31<06:08, 38.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1162/15290 [00:31<06:04, 38.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1166/15290 [00:31<06:04, 38.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1171/15290 [00:31<05:57, 39.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1175/15290 [00:31<06:01, 39.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1179/15290 [00:31<06:02, 38.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1184/15290 [00:31<05:53, 39.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1188/15290 [00:31<06:03, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1192/15290 [00:32<06:15, 37.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1196/15290 [00:32<06:23, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1200/15290 [00:32<06:25, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1204/15290 [00:32<06:28, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1208/15290 [00:32<06:30, 36.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1212/15290 [00:32<06:34, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1216/15290 [00:32<06:41, 35.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1220/15290 [00:32<06:38, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1225/15290 [00:32<06:18, 37.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1229/15290 [00:33<06:10, 37.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1233/15290 [00:33<06:09, 38.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1237/15290 [00:33<06:38, 35.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1241/15290 [00:33<06:37, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1245/15290 [00:33<06:44, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1250/15290 [00:33<06:19, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1255/15290 [00:33<06:05, 38.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1260/15290 [00:33<05:53, 39.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1264/15290 [00:33<06:01, 38.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1269/15290 [00:34<05:57, 39.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1274/15290 [00:34<05:52, 39.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1278/15290 [00:34<05:59, 39.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1282/15290 [00:34<06:12, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1286/15290 [00:34<06:15, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1291/15290 [00:34<06:01, 38.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1295/15290 [00:34<06:01, 38.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
8%|▊ | 1299/15290 [00:34<06:05, 38.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1304/15290 [00:35<05:52, 39.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1308/15290 [00:35<05:51, 39.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1312/15290 [00:35<05:52, 39.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1317/15290 [00:35<05:48, 40.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1322/15290 [00:35<05:55, 39.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1326/15290 [00:35<05:57, 39.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1330/15290 [00:35<05:58, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▊ | 1334/15290 [00:35<06:04, 38.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1338/15290 [00:35<06:10, 37.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1342/15290 [00:35<06:04, 38.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1346/15290 [00:36<06:01, 38.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1350/15290 [00:36<06:16, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1354/15290 [00:36<06:13, 37.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1358/15290 [00:36<06:21, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1362/15290 [00:36<06:28, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1366/15290 [00:36<06:22, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1370/15290 [00:36<06:25, 36.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1374/15290 [00:36<06:34, 35.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1378/15290 [00:36<06:30, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1382/15290 [00:37<06:31, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1386/15290 [00:37<06:31, 35.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1390/15290 [00:37<06:31, 35.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1394/15290 [00:37<06:41, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1398/15290 [00:37<06:37, 34.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1402/15290 [00:37<06:34, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1406/15290 [00:37<06:43, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1410/15290 [00:37<06:46, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1414/15290 [00:38<06:44, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1418/15290 [00:38<06:44, 34.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1422/15290 [00:38<06:35, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1426/15290 [00:38<06:30, 35.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1430/15290 [00:38<06:52, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1434/15290 [00:38<06:41, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1438/15290 [00:38<06:43, 34.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1442/15290 [00:38<06:36, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1446/15290 [00:38<06:25, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
9%|▉ | 1450/15290 [00:39<06:17, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1454/15290 [00:39<06:18, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1458/15290 [00:39<06:13, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1462/15290 [00:39<06:12, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1466/15290 [00:39<06:17, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1470/15290 [00:39<06:13, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1474/15290 [00:39<06:25, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1478/15290 [00:39<06:15, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1482/15290 [00:39<06:30, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1486/15290 [00:40<06:21, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1490/15290 [00:40<06:24, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1494/15290 [00:40<06:57, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1498/15290 [00:40<06:50, 33.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1502/15290 [00:40<06:42, 34.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1506/15290 [00:40<06:36, 34.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1510/15290 [00:40<06:38, 34.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1514/15290 [00:40<06:31, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1518/15290 [00:40<06:22, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1522/15290 [00:41<06:27, 35.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|▉ | 1526/15290 [00:41<06:23, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1530/15290 [00:41<06:15, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1534/15290 [00:41<06:08, 37.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1538/15290 [00:41<06:20, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1542/15290 [00:41<06:23, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1546/15290 [00:41<06:26, 35.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1550/15290 [00:41<06:22, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1554/15290 [00:41<06:18, 36.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1558/15290 [00:42<06:18, 36.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1562/15290 [00:42<06:15, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1566/15290 [00:42<06:17, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1570/15290 [00:42<06:16, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1574/15290 [00:42<06:10, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1578/15290 [00:42<06:15, 36.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1582/15290 [00:42<06:05, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1586/15290 [00:42<06:07, 37.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1591/15290 [00:42<05:56, 38.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1595/15290 [00:43<08:11, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1599/15290 [00:43<08:00, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
10%|█ | 1603/15290 [00:43<07:32, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1607/15290 [00:43<07:37, 29.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1611/15290 [00:43<07:08, 31.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1615/15290 [00:43<06:45, 33.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1619/15290 [00:43<06:27, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1623/15290 [00:43<06:21, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1627/15290 [00:44<06:19, 35.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1631/15290 [00:44<06:52, 33.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1635/15290 [00:44<06:50, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1640/15290 [00:44<06:23, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1644/15290 [00:44<06:19, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1648/15290 [00:44<06:38, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1652/15290 [00:44<06:48, 33.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1656/15290 [00:44<06:36, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1660/15290 [00:45<06:39, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1664/15290 [00:45<06:22, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1668/15290 [00:45<06:29, 34.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1672/15290 [00:45<06:26, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1676/15290 [00:45<06:13, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1681/15290 [00:45<06:00, 37.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1686/15290 [00:45<05:50, 38.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1690/15290 [00:45<05:59, 37.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1694/15290 [00:45<06:04, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1698/15290 [00:46<06:05, 37.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1702/15290 [00:46<05:59, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1706/15290 [00:46<05:53, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1711/15290 [00:46<05:45, 39.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1715/15290 [00:46<05:48, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█ | 1719/15290 [00:46<05:49, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1723/15290 [00:46<05:49, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1727/15290 [00:46<05:56, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1731/15290 [00:46<06:01, 37.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1735/15290 [00:47<05:54, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1739/15290 [00:47<05:53, 38.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1743/15290 [00:47<06:10, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1747/15290 [00:47<06:36, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1751/15290 [00:47<06:23, 35.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
11%|█▏ | 1755/15290 [00:47<06:13, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1759/15290 [00:47<06:05, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1763/15290 [00:47<06:09, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1767/15290 [00:47<06:09, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1771/15290 [00:48<06:00, 37.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1776/15290 [00:48<05:47, 38.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1780/15290 [00:48<06:05, 36.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1784/15290 [00:48<06:23, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1788/15290 [00:48<06:14, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1792/15290 [00:48<06:05, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1796/15290 [00:48<06:07, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1800/15290 [00:48<06:03, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1804/15290 [00:48<06:00, 37.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1808/15290 [00:49<06:05, 36.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1812/15290 [00:49<06:02, 37.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1816/15290 [00:49<06:14, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1820/15290 [00:49<06:12, 36.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1824/15290 [00:49<06:15, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1828/15290 [00:49<06:12, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1833/15290 [00:49<05:59, 37.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1837/15290 [00:49<06:20, 35.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1841/15290 [00:49<06:26, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1846/15290 [00:50<06:09, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1850/15290 [00:50<06:04, 36.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1854/15290 [00:50<05:58, 37.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1858/15290 [00:50<05:53, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1863/15290 [00:50<05:43, 39.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1867/15290 [00:50<05:47, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1871/15290 [00:50<05:44, 38.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1875/15290 [00:50<05:52, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1879/15290 [00:50<05:51, 38.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1883/15290 [00:51<05:51, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1887/15290 [00:51<05:48, 38.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1891/15290 [00:51<05:57, 37.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1895/15290 [00:51<05:51, 38.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1900/15290 [00:51<05:45, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1904/15290 [00:51<05:55, 37.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
12%|█▏ | 1908/15290 [00:51<06:00, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1912/15290 [00:51<06:11, 36.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1916/15290 [00:51<06:12, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1920/15290 [00:52<06:12, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1924/15290 [00:52<06:07, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1928/15290 [00:52<06:18, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1932/15290 [00:52<06:29, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1936/15290 [00:52<07:28, 29.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1940/15290 [00:52<07:25, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1944/15290 [00:52<06:56, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1948/15290 [00:52<06:33, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1952/15290 [00:53<06:22, 34.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1956/15290 [00:53<06:23, 34.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1960/15290 [00:53<06:17, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1964/15290 [00:53<06:15, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1968/15290 [00:53<06:11, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1972/15290 [00:53<06:20, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1976/15290 [00:53<06:14, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1980/15290 [00:53<06:11, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1984/15290 [00:53<06:21, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1988/15290 [00:54<06:20, 34.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1992/15290 [00:54<06:23, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 1996/15290 [00:54<06:12, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2000/15290 [00:54<06:04, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2004/15290 [00:54<05:59, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2008/15290 [00:54<06:15, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2012/15290 [00:54<07:28, 29.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2016/15290 [00:54<07:15, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2020/15290 [00:55<07:12, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2024/15290 [00:55<07:08, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2028/15290 [00:55<06:44, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2032/15290 [00:55<06:25, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2036/15290 [00:55<06:11, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2040/15290 [00:55<06:14, 35.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2044/15290 [00:55<06:04, 36.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2048/15290 [00:55<06:02, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2052/15290 [00:55<06:04, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2056/15290 [00:56<05:56, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2060/15290 [00:56<05:57, 37.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
13%|█▎ | 2064/15290 [00:56<06:07, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2068/15290 [00:56<06:03, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2072/15290 [00:56<05:57, 37.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2076/15290 [00:56<05:49, 37.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2080/15290 [00:56<07:09, 30.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2084/15290 [00:56<07:03, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2088/15290 [00:56<06:47, 32.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2092/15290 [00:57<06:35, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2096/15290 [00:57<06:21, 34.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▎ | 2100/15290 [00:57<06:13, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2104/15290 [00:57<06:15, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2108/15290 [00:57<06:19, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2112/15290 [00:57<06:26, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2116/15290 [00:57<06:29, 33.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2120/15290 [00:57<06:28, 33.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2124/15290 [00:58<06:18, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2128/15290 [00:58<06:15, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2132/15290 [00:58<06:04, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2136/15290 [00:58<06:05, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2140/15290 [00:58<05:59, 36.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2144/15290 [00:58<05:55, 36.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2148/15290 [00:58<05:52, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2152/15290 [00:58<06:00, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2156/15290 [00:58<06:01, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2160/15290 [00:58<06:08, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2164/15290 [00:59<06:04, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2168/15290 [00:59<05:57, 36.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2172/15290 [00:59<05:49, 37.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2176/15290 [00:59<05:50, 37.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2180/15290 [00:59<05:56, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2185/15290 [00:59<05:42, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2190/15290 [00:59<05:37, 38.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2194/15290 [00:59<05:34, 39.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2198/15290 [00:59<05:36, 38.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2202/15290 [01:00<05:38, 38.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2206/15290 [01:00<05:43, 38.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2210/15290 [01:00<05:40, 38.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
14%|█▍ | 2214/15290 [01:00<05:52, 37.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2218/15290 [01:00<05:58, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2222/15290 [01:00<06:15, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2226/15290 [01:00<06:17, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2230/15290 [01:00<06:11, 35.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2234/15290 [01:00<06:03, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2238/15290 [01:01<06:08, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2242/15290 [01:01<06:20, 34.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2246/15290 [01:01<06:18, 34.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2251/15290 [01:01<05:57, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2256/15290 [01:01<05:38, 38.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2260/15290 [01:01<05:39, 38.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2264/15290 [01:01<05:49, 37.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2268/15290 [01:01<05:54, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2272/15290 [01:02<05:57, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2276/15290 [01:02<05:52, 36.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2280/15290 [01:02<06:09, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2284/15290 [01:02<06:08, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2288/15290 [01:02<06:15, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▍ | 2292/15290 [01:02<06:54, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2296/15290 [01:02<06:33, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2300/15290 [01:02<06:14, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2305/15290 [01:02<05:55, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2309/15290 [01:03<05:48, 37.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2313/15290 [01:03<05:42, 37.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2317/15290 [01:03<05:37, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2321/15290 [01:03<06:14, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2325/15290 [01:03<06:06, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2329/15290 [01:03<05:55, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2334/15290 [01:03<05:42, 37.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2338/15290 [01:03<05:45, 37.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2342/15290 [01:03<05:43, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2346/15290 [01:04<05:41, 37.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2350/15290 [01:04<05:41, 37.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2354/15290 [01:04<05:51, 36.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2358/15290 [01:04<05:51, 36.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2362/15290 [01:04<05:44, 37.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
15%|█▌ | 2366/15290 [01:04<05:45, 37.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2370/15290 [01:04<05:49, 36.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2374/15290 [01:04<05:55, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2378/15290 [01:04<05:51, 36.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2382/15290 [01:05<05:49, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2386/15290 [01:05<05:50, 36.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2390/15290 [01:05<05:42, 37.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2394/15290 [01:05<05:48, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2399/15290 [01:05<05:37, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2403/15290 [01:05<05:43, 37.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2407/15290 [01:05<05:48, 36.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2411/15290 [01:05<05:42, 37.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2415/15290 [01:05<05:38, 38.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2419/15290 [01:06<05:34, 38.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2423/15290 [01:06<05:49, 36.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2427/15290 [01:06<05:50, 36.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2431/15290 [01:06<05:46, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2435/15290 [01:06<05:40, 37.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2440/15290 [01:06<05:30, 38.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2444/15290 [01:06<05:31, 38.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2448/15290 [01:06<05:41, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2452/15290 [01:06<05:38, 37.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2457/15290 [01:07<05:29, 38.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2461/15290 [01:07<05:35, 38.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2465/15290 [01:07<05:58, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2469/15290 [01:07<05:52, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2473/15290 [01:07<05:48, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2477/15290 [01:07<05:48, 36.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▌ | 2481/15290 [01:07<05:50, 36.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2485/15290 [01:07<05:54, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2489/15290 [01:07<05:59, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2493/15290 [01:08<05:48, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2497/15290 [01:08<05:50, 36.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2501/15290 [01:08<05:43, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2505/15290 [01:08<05:42, 37.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2509/15290 [01:08<05:55, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2513/15290 [01:08<06:09, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2517/15290 [01:08<06:06, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
16%|█▋ | 2521/15290 [01:08<06:10, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2525/15290 [01:08<06:13, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2529/15290 [01:09<06:07, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2533/15290 [01:09<06:15, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2537/15290 [01:09<06:26, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2541/15290 [01:09<06:17, 33.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2545/15290 [01:09<06:21, 33.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2549/15290 [01:09<06:15, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2553/15290 [01:09<05:59, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2557/15290 [01:09<05:49, 36.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2561/15290 [01:09<05:43, 37.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2565/15290 [01:10<05:45, 36.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2569/15290 [01:10<05:41, 37.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2573/15290 [01:10<05:46, 36.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2577/15290 [01:10<05:49, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2581/15290 [01:10<05:59, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2585/15290 [01:10<06:11, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2589/15290 [01:10<06:17, 33.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2593/15290 [01:10<06:18, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2597/15290 [01:11<06:24, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2601/15290 [01:11<06:15, 33.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2605/15290 [01:11<06:30, 32.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2609/15290 [01:11<06:37, 31.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2613/15290 [01:11<06:29, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2617/15290 [01:11<06:26, 32.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2621/15290 [01:11<06:19, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2625/15290 [01:11<06:17, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2629/15290 [01:11<06:18, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2633/15290 [01:12<06:08, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2637/15290 [01:12<06:04, 34.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2641/15290 [01:12<05:54, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2645/15290 [01:12<05:51, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2649/15290 [01:12<05:49, 36.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2653/15290 [01:12<05:45, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2657/15290 [01:12<05:51, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2661/15290 [01:12<05:49, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2665/15290 [01:13<06:48, 30.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2669/15290 [01:13<06:39, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
17%|█▋ | 2673/15290 [01:13<06:19, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2677/15290 [01:13<06:15, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2681/15290 [01:13<06:06, 34.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2685/15290 [01:13<06:09, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2689/15290 [01:13<06:10, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2693/15290 [01:13<06:07, 34.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2697/15290 [01:13<05:53, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2702/15290 [01:14<05:39, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2706/15290 [01:14<05:33, 37.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2710/15290 [01:14<05:39, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2714/15290 [01:14<05:39, 37.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2718/15290 [01:14<05:45, 36.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2722/15290 [01:14<05:57, 35.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2726/15290 [01:14<06:03, 34.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2730/15290 [01:14<06:08, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2734/15290 [01:14<06:10, 33.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2738/15290 [01:15<06:05, 34.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2742/15290 [01:15<06:06, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2746/15290 [01:15<06:07, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2750/15290 [01:15<05:59, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2754/15290 [01:15<05:55, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2758/15290 [01:15<05:49, 35.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2762/15290 [01:15<06:05, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2766/15290 [01:15<06:02, 34.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2770/15290 [01:16<05:54, 35.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2774/15290 [01:16<05:45, 36.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2778/15290 [01:16<05:45, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2782/15290 [01:16<05:39, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2786/15290 [01:16<05:34, 37.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2790/15290 [01:16<05:29, 37.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2794/15290 [01:16<05:27, 38.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2798/15290 [01:16<05:39, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2802/15290 [01:16<05:43, 36.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2806/15290 [01:16<05:40, 36.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2810/15290 [01:17<05:32, 37.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2814/15290 [01:17<05:35, 37.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2819/15290 [01:17<05:24, 38.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2823/15290 [01:17<05:22, 38.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
18%|█▊ | 2827/15290 [01:17<05:23, 38.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2831/15290 [01:17<05:23, 38.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2835/15290 [01:17<05:28, 37.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2839/15290 [01:17<05:45, 36.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2843/15290 [01:17<05:44, 36.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2847/15290 [01:18<05:48, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2851/15290 [01:18<05:46, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2855/15290 [01:18<05:40, 36.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2859/15290 [01:18<05:42, 36.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▊ | 2863/15290 [01:18<05:39, 36.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2867/15290 [01:18<05:39, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2871/15290 [01:18<05:36, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2875/15290 [01:18<05:37, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2879/15290 [01:18<05:35, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2883/15290 [01:19<05:34, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2887/15290 [01:19<05:33, 37.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2891/15290 [01:19<05:34, 37.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2895/15290 [01:19<05:33, 37.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2899/15290 [01:19<05:41, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2903/15290 [01:19<05:56, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2907/15290 [01:19<06:03, 34.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2911/15290 [01:19<06:11, 33.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2915/15290 [01:19<06:17, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2919/15290 [01:20<06:06, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2923/15290 [01:20<05:57, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2927/15290 [01:20<05:59, 34.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2931/15290 [01:20<05:58, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2936/15290 [01:20<05:43, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2940/15290 [01:20<05:53, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2944/15290 [01:20<05:58, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2948/15290 [01:20<06:32, 31.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2952/15290 [01:21<06:31, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2956/15290 [01:21<06:31, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2960/15290 [01:21<06:15, 32.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2964/15290 [01:21<06:04, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2968/15290 [01:21<05:52, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2972/15290 [01:21<05:55, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2976/15290 [01:21<05:54, 34.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
19%|█▉ | 2980/15290 [01:21<06:00, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 2984/15290 [01:22<05:55, 34.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 2988/15290 [01:22<06:00, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 2992/15290 [01:22<06:01, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 2996/15290 [01:22<06:06, 33.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3000/15290 [01:22<06:09, 33.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3004/15290 [01:22<06:11, 33.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3008/15290 [01:22<06:10, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3012/15290 [01:22<06:08, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3016/15290 [01:22<05:59, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3020/15290 [01:23<05:50, 34.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3024/15290 [01:23<05:43, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3028/15290 [01:23<05:39, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3032/15290 [01:23<05:32, 36.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3036/15290 [01:23<05:32, 36.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3040/15290 [01:23<06:01, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3044/15290 [01:23<05:58, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3048/15290 [01:23<06:09, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3052/15290 [01:24<06:13, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|█▉ | 3056/15290 [01:24<06:01, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3060/15290 [01:24<05:57, 34.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3064/15290 [01:24<06:04, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3068/15290 [01:24<05:54, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3072/15290 [01:24<05:53, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3076/15290 [01:24<05:58, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3080/15290 [01:24<05:57, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3084/15290 [01:24<05:58, 34.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3088/15290 [01:25<05:49, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3092/15290 [01:25<05:57, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3096/15290 [01:25<05:55, 34.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3100/15290 [01:25<06:01, 33.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3104/15290 [01:25<05:55, 34.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3108/15290 [01:25<05:56, 34.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3112/15290 [01:25<05:55, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3116/15290 [01:25<05:52, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3120/15290 [01:25<05:59, 33.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3124/15290 [01:26<06:06, 33.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3128/15290 [01:26<06:08, 33.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
20%|██ | 3132/15290 [01:26<06:13, 32.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3136/15290 [01:26<06:04, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3140/15290 [01:26<06:09, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3144/15290 [01:26<06:08, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3148/15290 [01:26<06:25, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3152/15290 [01:27<06:29, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3156/15290 [01:27<06:42, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3160/15290 [01:27<06:38, 30.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3164/15290 [01:27<06:37, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3168/15290 [01:27<06:36, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3172/15290 [01:27<06:36, 30.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3176/15290 [01:27<07:07, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3180/15290 [01:27<06:42, 30.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3184/15290 [01:28<06:29, 31.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3188/15290 [01:28<06:16, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3192/15290 [01:28<06:12, 32.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3196/15290 [01:28<06:08, 32.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3200/15290 [01:28<06:05, 33.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3204/15290 [01:28<05:50, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3208/15290 [01:28<05:47, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3212/15290 [01:28<06:14, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3216/15290 [01:29<06:17, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3220/15290 [01:29<06:07, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3224/15290 [01:29<05:55, 33.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3228/15290 [01:29<06:40, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3232/15290 [01:29<06:37, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3236/15290 [01:29<06:24, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3240/15290 [01:29<06:18, 31.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3244/15290 [01:29<06:13, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██ | 3248/15290 [01:30<06:08, 32.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3252/15290 [01:30<06:07, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3256/15290 [01:30<06:07, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3260/15290 [01:30<06:02, 33.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3264/15290 [01:30<05:53, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3268/15290 [01:30<05:46, 34.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3272/15290 [01:30<05:44, 34.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3276/15290 [01:30<05:39, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3280/15290 [01:30<05:31, 36.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
21%|██▏ | 3284/15290 [01:31<05:34, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3288/15290 [01:31<05:37, 35.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3292/15290 [01:31<05:36, 35.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3296/15290 [01:31<05:37, 35.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3300/15290 [01:31<05:42, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3304/15290 [01:31<05:35, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3308/15290 [01:31<05:31, 36.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3312/15290 [01:31<05:34, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3316/15290 [01:31<05:31, 36.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3320/15290 [01:32<06:07, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3324/15290 [01:32<05:54, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3328/15290 [01:32<05:46, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3332/15290 [01:32<05:38, 35.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3336/15290 [01:32<05:38, 35.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3340/15290 [01:32<05:28, 36.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3344/15290 [01:32<05:19, 37.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3349/15290 [01:32<05:10, 38.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3353/15290 [01:32<05:13, 38.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3357/15290 [01:33<05:50, 34.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3361/15290 [01:33<05:42, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3365/15290 [01:33<05:34, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3369/15290 [01:33<05:25, 36.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3373/15290 [01:33<05:27, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3377/15290 [01:33<05:25, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3381/15290 [01:33<05:22, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3385/15290 [01:33<05:22, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3389/15290 [01:33<05:18, 37.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3393/15290 [01:34<05:23, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3397/15290 [01:34<05:21, 36.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3401/15290 [01:34<05:33, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3405/15290 [01:34<05:23, 36.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3409/15290 [01:34<05:22, 36.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3413/15290 [01:34<05:19, 37.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3417/15290 [01:34<05:15, 37.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3421/15290 [01:34<05:11, 38.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3425/15290 [01:34<05:08, 38.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3429/15290 [01:35<05:13, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3433/15290 [01:35<05:15, 37.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
22%|██▏ | 3437/15290 [01:35<05:09, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3441/15290 [01:35<05:10, 38.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3445/15290 [01:35<05:06, 38.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3449/15290 [01:35<05:04, 38.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3453/15290 [01:35<05:14, 37.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3457/15290 [01:35<05:09, 38.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3461/15290 [01:35<05:08, 38.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3465/15290 [01:35<05:06, 38.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3469/15290 [01:36<05:12, 37.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3473/15290 [01:36<05:31, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3477/15290 [01:36<05:40, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3481/15290 [01:36<05:35, 35.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3485/15290 [01:36<05:25, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3489/15290 [01:36<05:19, 36.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3493/15290 [01:36<05:16, 37.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3497/15290 [01:36<05:12, 37.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3501/15290 [01:36<05:08, 38.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3505/15290 [01:37<05:08, 38.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3509/15290 [01:37<05:14, 37.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3513/15290 [01:37<05:20, 36.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3517/15290 [01:37<05:26, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3521/15290 [01:37<05:24, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3525/15290 [01:37<05:23, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3529/15290 [01:37<05:27, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3533/15290 [01:37<05:37, 34.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3537/15290 [01:37<05:29, 35.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3541/15290 [01:38<05:27, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3545/15290 [01:38<05:38, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3549/15290 [01:38<05:36, 34.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3553/15290 [01:38<05:29, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3557/15290 [01:38<05:23, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3561/15290 [01:38<05:20, 36.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3565/15290 [01:38<05:18, 36.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3569/15290 [01:38<05:21, 36.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3573/15290 [01:38<05:21, 36.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3577/15290 [01:39<05:19, 36.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3581/15290 [01:39<05:16, 36.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3585/15290 [01:39<05:14, 37.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3589/15290 [01:39<05:21, 36.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
23%|██▎ | 3593/15290 [01:39<05:25, 35.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3597/15290 [01:39<05:22, 36.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3601/15290 [01:39<05:23, 36.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3605/15290 [01:39<05:40, 34.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3609/15290 [01:39<05:48, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3613/15290 [01:40<05:41, 34.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3617/15290 [01:40<05:42, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3621/15290 [01:40<05:42, 34.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3625/15290 [01:40<05:42, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▎ | 3629/15290 [01:40<05:51, 33.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3633/15290 [01:40<05:55, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3637/15290 [01:40<06:03, 32.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3641/15290 [01:40<06:12, 31.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3645/15290 [01:41<06:22, 30.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3649/15290 [01:41<06:31, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3653/15290 [01:41<06:25, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3657/15290 [01:41<06:12, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3661/15290 [01:41<06:01, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3665/15290 [01:41<05:53, 32.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3669/15290 [01:41<05:47, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3673/15290 [01:41<05:34, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3677/15290 [01:42<05:28, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3681/15290 [01:42<05:28, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3685/15290 [01:42<05:33, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3689/15290 [01:42<05:21, 36.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3693/15290 [01:42<05:20, 36.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3697/15290 [01:42<05:24, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3701/15290 [01:42<05:30, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3705/15290 [01:42<05:30, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3709/15290 [01:42<05:28, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3713/15290 [01:43<05:35, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3717/15290 [01:43<05:36, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3721/15290 [01:43<05:35, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3725/15290 [01:43<05:35, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3729/15290 [01:43<06:17, 30.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3733/15290 [01:43<06:09, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3737/15290 [01:43<05:50, 32.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3741/15290 [01:43<05:41, 33.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
24%|██▍ | 3745/15290 [01:44<05:31, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3749/15290 [01:44<05:23, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3753/15290 [01:44<05:24, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3757/15290 [01:44<05:23, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3761/15290 [01:44<05:25, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3765/15290 [01:44<05:20, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3769/15290 [01:44<05:20, 36.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3773/15290 [01:44<05:23, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3777/15290 [01:44<05:27, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3781/15290 [01:45<05:25, 35.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3785/15290 [01:45<05:17, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3789/15290 [01:45<05:19, 35.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3793/15290 [01:45<05:41, 33.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3797/15290 [01:45<06:05, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3801/15290 [01:45<06:10, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3805/15290 [01:45<06:07, 31.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3809/15290 [01:45<05:56, 32.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3813/15290 [01:46<05:43, 33.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3817/15290 [01:46<05:42, 33.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▍ | 3821/15290 [01:46<05:54, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3825/15290 [01:46<05:51, 32.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3829/15290 [01:46<05:45, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3833/15290 [01:46<05:43, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3837/15290 [01:46<05:38, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3841/15290 [01:46<05:48, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3845/15290 [01:46<05:43, 33.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3849/15290 [01:47<05:36, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3853/15290 [01:47<05:43, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3857/15290 [01:47<05:33, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3861/15290 [01:47<05:24, 35.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3865/15290 [01:47<05:51, 32.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3869/15290 [01:47<05:54, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3873/15290 [01:47<05:52, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3877/15290 [01:47<05:42, 33.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3881/15290 [01:48<05:31, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3885/15290 [01:48<05:25, 34.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3889/15290 [01:48<05:22, 35.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3893/15290 [01:48<05:22, 35.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
25%|██▌ | 3897/15290 [01:48<05:16, 36.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3901/15290 [01:48<05:13, 36.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3905/15290 [01:48<05:19, 35.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3909/15290 [01:48<05:34, 34.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3913/15290 [01:48<05:38, 33.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3917/15290 [01:49<05:41, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3921/15290 [01:49<05:45, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3925/15290 [01:49<06:00, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3929/15290 [01:49<05:50, 32.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3933/15290 [01:49<05:38, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3937/15290 [01:49<05:28, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3941/15290 [01:49<05:24, 34.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3945/15290 [01:49<05:23, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3949/15290 [01:50<05:23, 35.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3953/15290 [01:50<05:26, 34.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3957/15290 [01:50<05:25, 34.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3961/15290 [01:50<05:36, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3965/15290 [01:50<05:33, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3969/15290 [01:50<05:35, 33.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3973/15290 [01:50<05:24, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3977/15290 [01:50<05:26, 34.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3981/15290 [01:50<05:25, 34.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3985/15290 [01:51<05:16, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3989/15290 [01:51<05:22, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3993/15290 [01:51<05:27, 34.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 3997/15290 [01:51<05:28, 34.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 4001/15290 [01:51<05:36, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 4005/15290 [01:51<05:37, 33.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 4009/15290 [01:51<05:38, 33.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▌ | 4013/15290 [01:51<05:35, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4017/15290 [01:52<05:28, 34.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4021/15290 [01:52<05:25, 34.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4025/15290 [01:52<05:15, 35.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4029/15290 [01:52<05:18, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4033/15290 [01:52<05:15, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4037/15290 [01:52<05:20, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4041/15290 [01:52<05:15, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4045/15290 [01:52<05:12, 35.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
26%|██▋ | 4049/15290 [01:52<05:09, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4053/15290 [01:53<05:08, 36.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4057/15290 [01:53<05:07, 36.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4061/15290 [01:53<05:10, 36.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4065/15290 [01:53<05:03, 36.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4069/15290 [01:53<05:00, 37.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4073/15290 [01:53<05:00, 37.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4077/15290 [01:53<05:02, 37.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4081/15290 [01:53<04:58, 37.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4085/15290 [01:53<05:02, 37.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4089/15290 [01:54<05:13, 35.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4093/15290 [01:54<05:10, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4097/15290 [01:54<05:15, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4101/15290 [01:54<05:32, 33.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4105/15290 [01:54<05:30, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4109/15290 [01:54<05:29, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4113/15290 [01:54<05:35, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4117/15290 [01:54<05:34, 33.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4121/15290 [01:54<05:26, 34.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4125/15290 [01:55<05:22, 34.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4129/15290 [01:55<05:24, 34.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4133/15290 [01:55<05:26, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4137/15290 [01:55<05:20, 34.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4141/15290 [01:55<05:29, 33.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4145/15290 [01:55<05:26, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4149/15290 [01:55<05:26, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4153/15290 [01:55<05:57, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4157/15290 [01:56<05:47, 32.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4161/15290 [01:56<05:50, 31.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4165/15290 [01:56<05:45, 32.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4169/15290 [01:56<05:45, 32.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4173/15290 [01:56<05:46, 32.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4177/15290 [01:56<05:35, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4181/15290 [01:56<05:32, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4185/15290 [01:56<05:25, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4189/15290 [01:57<05:36, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4193/15290 [01:57<05:39, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4197/15290 [01:57<05:42, 32.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
27%|██▋ | 4201/15290 [01:57<05:35, 33.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4205/15290 [01:57<05:30, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4209/15290 [01:57<05:24, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4213/15290 [01:57<05:29, 33.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4217/15290 [01:57<05:35, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4221/15290 [01:57<05:39, 32.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4225/15290 [01:58<05:37, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4229/15290 [01:58<05:30, 33.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4233/15290 [01:58<05:28, 33.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4237/15290 [01:58<05:30, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4241/15290 [01:58<05:28, 33.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4245/15290 [01:58<05:20, 34.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4249/15290 [01:58<05:17, 34.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4253/15290 [01:58<05:24, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4257/15290 [01:59<05:23, 34.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4261/15290 [01:59<05:14, 35.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4265/15290 [01:59<05:21, 34.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4269/15290 [01:59<05:34, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4273/15290 [01:59<05:28, 33.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4277/15290 [01:59<05:21, 34.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4281/15290 [01:59<05:23, 34.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4285/15290 [01:59<05:33, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4289/15290 [01:59<05:30, 33.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4293/15290 [02:00<05:40, 32.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4297/15290 [02:00<05:32, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4301/15290 [02:00<05:37, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4305/15290 [02:00<05:39, 32.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4309/15290 [02:00<05:44, 31.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4313/15290 [02:00<05:45, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4317/15290 [02:00<05:51, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4321/15290 [02:01<05:55, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4325/15290 [02:01<05:56, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4329/15290 [02:01<05:55, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4333/15290 [02:01<05:55, 30.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4337/15290 [02:01<05:50, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4341/15290 [02:01<06:00, 30.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4345/15290 [02:01<05:54, 30.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4349/15290 [02:01<05:51, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4353/15290 [02:02<05:55, 30.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
28%|██▊ | 4357/15290 [02:02<05:44, 31.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4361/15290 [02:02<05:42, 31.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4365/15290 [02:02<05:43, 31.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4369/15290 [02:02<05:39, 32.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4373/15290 [02:02<05:29, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4377/15290 [02:02<05:28, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4381/15290 [02:02<05:26, 33.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4385/15290 [02:03<05:23, 33.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4389/15290 [02:03<05:18, 34.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▊ | 4393/15290 [02:03<05:12, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4397/15290 [02:03<05:05, 35.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4401/15290 [02:03<05:22, 33.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4405/15290 [02:03<05:24, 33.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4409/15290 [02:03<05:24, 33.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4413/15290 [02:03<05:28, 33.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4417/15290 [02:03<05:24, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4421/15290 [02:04<05:17, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4425/15290 [02:04<05:21, 33.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4429/15290 [02:04<05:19, 33.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4433/15290 [02:04<05:32, 32.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4437/15290 [02:04<05:27, 33.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4441/15290 [02:04<05:20, 33.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4445/15290 [02:04<05:19, 33.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4449/15290 [02:04<05:25, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4453/15290 [02:05<05:28, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4457/15290 [02:05<05:30, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4461/15290 [02:05<05:26, 33.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4465/15290 [02:05<05:28, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4469/15290 [02:05<05:32, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4473/15290 [02:05<05:34, 32.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4477/15290 [02:05<05:27, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4481/15290 [02:05<05:27, 33.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4485/15290 [02:05<05:24, 33.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4489/15290 [02:06<05:22, 33.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4493/15290 [02:06<05:31, 32.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4497/15290 [02:06<05:34, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4501/15290 [02:06<05:48, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4505/15290 [02:06<05:37, 31.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
29%|██▉ | 4509/15290 [02:06<05:40, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4513/15290 [02:06<05:34, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4517/15290 [02:06<05:23, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4521/15290 [02:07<05:13, 34.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4525/15290 [02:07<05:07, 35.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4529/15290 [02:07<05:12, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4533/15290 [02:07<05:10, 34.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4537/15290 [02:07<05:06, 35.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4541/15290 [02:07<05:06, 35.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4545/15290 [02:07<05:37, 31.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4549/15290 [02:07<05:33, 32.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4553/15290 [02:08<05:19, 33.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4557/15290 [02:08<05:22, 33.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4561/15290 [02:08<05:15, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4565/15290 [02:08<05:04, 35.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4569/15290 [02:08<04:59, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4573/15290 [02:08<04:58, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4577/15290 [02:08<04:54, 36.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4581/15290 [02:08<04:53, 36.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|██▉ | 4585/15290 [02:08<05:08, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4589/15290 [02:09<05:13, 34.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4593/15290 [02:09<05:09, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4597/15290 [02:09<05:05, 34.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4601/15290 [02:09<05:04, 35.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4605/15290 [02:09<05:00, 35.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4609/15290 [02:09<04:59, 35.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4613/15290 [02:09<04:59, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4617/15290 [02:09<04:58, 35.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4621/15290 [02:09<04:57, 35.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4625/15290 [02:10<04:55, 36.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4629/15290 [02:10<05:03, 35.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4633/15290 [02:10<05:21, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4637/15290 [02:10<05:43, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4641/15290 [02:10<05:59, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4645/15290 [02:10<05:56, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4649/15290 [02:10<05:51, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4653/15290 [02:10<05:40, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4657/15290 [02:11<05:53, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
30%|███ | 4661/15290 [02:11<05:55, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4665/15290 [02:11<05:45, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4669/15290 [02:11<05:27, 32.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4673/15290 [02:11<05:35, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4677/15290 [02:11<05:23, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4681/15290 [02:11<05:37, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4685/15290 [02:12<05:36, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4689/15290 [02:12<05:23, 32.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4693/15290 [02:12<05:25, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4697/15290 [02:12<05:18, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4701/15290 [02:12<05:22, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4705/15290 [02:12<05:28, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4709/15290 [02:12<05:15, 33.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4713/15290 [02:12<05:29, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4717/15290 [02:12<05:27, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4721/15290 [02:13<05:39, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4725/15290 [02:13<05:33, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4729/15290 [02:13<05:30, 31.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4733/15290 [02:13<05:27, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4737/15290 [02:13<05:14, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4741/15290 [02:13<05:24, 32.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4745/15290 [02:13<05:27, 32.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4749/15290 [02:13<05:35, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4753/15290 [02:14<05:48, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4757/15290 [02:14<05:38, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4761/15290 [02:14<05:44, 30.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4765/15290 [02:14<05:39, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4769/15290 [02:14<05:52, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4773/15290 [02:14<05:53, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███ | 4776/15290 [02:14<05:56, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4780/15290 [02:15<05:42, 30.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4784/15290 [02:15<05:46, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4788/15290 [02:15<05:38, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4792/15290 [02:15<05:30, 31.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4796/15290 [02:15<05:32, 31.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4800/15290 [02:15<05:15, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4804/15290 [02:15<05:30, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4808/15290 [02:15<05:29, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4812/15290 [02:16<05:32, 31.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
31%|███▏ | 4816/15290 [02:16<05:39, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4820/15290 [02:16<05:26, 32.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4824/15290 [02:16<05:30, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4828/15290 [02:16<05:19, 32.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4832/15290 [02:16<05:16, 33.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4836/15290 [02:16<05:25, 32.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4840/15290 [02:16<05:14, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4844/15290 [02:16<05:06, 34.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4848/15290 [02:17<05:29, 31.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4852/15290 [02:17<05:19, 32.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4856/15290 [02:17<05:26, 31.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4860/15290 [02:17<05:27, 31.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4864/15290 [02:17<05:31, 31.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4868/15290 [02:17<05:36, 30.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4872/15290 [02:17<05:17, 32.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4876/15290 [02:17<05:08, 33.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4880/15290 [02:18<04:56, 35.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4884/15290 [02:18<04:52, 35.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4888/15290 [02:18<04:51, 35.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4892/15290 [02:18<04:58, 34.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4896/15290 [02:18<05:11, 33.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4900/15290 [02:18<05:15, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4904/15290 [02:18<05:18, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4908/15290 [02:18<05:26, 31.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4912/15290 [02:19<05:11, 33.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4916/15290 [02:19<05:08, 33.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4920/15290 [02:19<05:07, 33.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4924/15290 [02:19<05:42, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4928/15290 [02:19<05:41, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4932/15290 [02:19<05:31, 31.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4936/15290 [02:19<05:20, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4940/15290 [02:19<05:46, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4944/15290 [02:20<05:36, 30.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4948/15290 [02:20<05:24, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4952/15290 [02:20<05:10, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4956/15290 [02:20<05:00, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4960/15290 [02:20<04:55, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4964/15290 [02:20<04:52, 35.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
32%|███▏ | 4968/15290 [02:20<04:48, 35.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4972/15290 [02:20<04:45, 36.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4976/15290 [02:20<04:46, 36.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4980/15290 [02:21<04:46, 35.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4984/15290 [02:21<04:47, 35.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4988/15290 [02:21<04:44, 36.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4992/15290 [02:21<04:41, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 4996/15290 [02:21<04:37, 37.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5000/15290 [02:21<04:37, 37.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5004/15290 [02:21<04:37, 37.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5008/15290 [02:21<04:36, 37.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5012/15290 [02:21<04:35, 37.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5016/15290 [02:22<04:36, 37.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5020/15290 [02:22<04:46, 35.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5024/15290 [02:22<05:05, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5028/15290 [02:22<05:17, 32.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5032/15290 [02:22<05:40, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5036/15290 [02:22<05:21, 31.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5040/15290 [02:22<05:11, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5044/15290 [02:22<05:02, 33.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5048/15290 [02:23<05:00, 34.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5052/15290 [02:23<04:57, 34.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5056/15290 [02:23<04:52, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5060/15290 [02:23<05:36, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5064/15290 [02:23<05:22, 31.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5068/15290 [02:23<05:06, 33.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5072/15290 [02:23<05:00, 34.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5076/15290 [02:23<05:15, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5080/15290 [02:24<05:20, 31.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5084/15290 [02:24<05:09, 32.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5088/15290 [02:24<05:10, 32.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5092/15290 [02:24<05:30, 30.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5096/15290 [02:24<05:23, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5100/15290 [02:24<05:23, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5104/15290 [02:24<05:29, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5108/15290 [02:24<05:15, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5112/15290 [02:25<05:05, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5116/15290 [02:25<04:58, 34.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
33%|███▎ | 5120/15290 [02:25<04:58, 34.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5124/15290 [02:25<04:56, 34.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5128/15290 [02:25<04:59, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5132/15290 [02:25<04:57, 34.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5136/15290 [02:25<04:54, 34.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5140/15290 [02:25<04:51, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5144/15290 [02:25<04:44, 35.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5148/15290 [02:26<04:38, 36.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5152/15290 [02:26<04:39, 36.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5156/15290 [02:26<04:37, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▎ | 5160/15290 [02:26<04:36, 36.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5164/15290 [02:26<04:42, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5168/15290 [02:26<04:44, 35.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5172/15290 [02:26<04:41, 35.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5176/15290 [02:26<04:53, 34.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5180/15290 [02:26<04:48, 35.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5184/15290 [02:27<04:44, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5188/15290 [02:27<04:38, 36.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5192/15290 [02:27<04:36, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5196/15290 [02:27<04:40, 35.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5200/15290 [02:27<04:49, 34.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5204/15290 [02:27<04:45, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5208/15290 [02:27<04:45, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5212/15290 [02:27<05:05, 32.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5216/15290 [02:28<05:11, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5220/15290 [02:28<05:11, 32.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5224/15290 [02:28<05:01, 33.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5228/15290 [02:28<04:55, 34.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5232/15290 [02:28<04:51, 34.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5236/15290 [02:28<04:56, 33.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5240/15290 [02:28<04:57, 33.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5244/15290 [02:28<05:04, 32.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5248/15290 [02:28<05:02, 33.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5252/15290 [02:29<05:01, 33.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5256/15290 [02:29<05:03, 33.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5260/15290 [02:29<05:02, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5264/15290 [02:29<05:09, 32.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5268/15290 [02:29<05:06, 32.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
34%|███▍ | 5272/15290 [02:29<05:00, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5276/15290 [02:29<05:28, 30.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5280/15290 [02:29<05:26, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5284/15290 [02:30<05:13, 31.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5288/15290 [02:30<05:05, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5292/15290 [02:30<05:06, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5296/15290 [02:30<05:11, 32.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5300/15290 [02:30<05:15, 31.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5304/15290 [02:30<05:15, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5308/15290 [02:30<05:09, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5312/15290 [02:30<05:05, 32.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5316/15290 [02:31<05:05, 32.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5320/15290 [02:31<05:02, 33.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5324/15290 [02:31<04:58, 33.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5328/15290 [02:31<04:51, 34.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5332/15290 [02:31<04:46, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5336/15290 [02:31<04:42, 35.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5340/15290 [02:31<04:43, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5344/15290 [02:31<04:40, 35.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▍ | 5348/15290 [02:31<04:43, 35.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5352/15290 [02:32<04:40, 35.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5356/15290 [02:32<04:44, 34.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5360/15290 [02:32<04:38, 35.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5364/15290 [02:32<04:46, 34.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5368/15290 [02:32<04:48, 34.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5372/15290 [02:32<04:44, 34.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5376/15290 [02:32<04:46, 34.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5380/15290 [02:32<04:45, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5384/15290 [02:33<04:42, 35.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5388/15290 [02:33<04:39, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5392/15290 [02:33<04:36, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5396/15290 [02:33<04:36, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5400/15290 [02:33<04:41, 35.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5404/15290 [02:33<04:41, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5408/15290 [02:33<04:38, 35.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5412/15290 [02:33<04:35, 35.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5416/15290 [02:33<04:29, 36.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5420/15290 [02:33<04:30, 36.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
35%|███▌ | 5424/15290 [02:34<04:29, 36.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5428/15290 [02:34<04:28, 36.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5432/15290 [02:34<04:30, 36.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5436/15290 [02:34<04:28, 36.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5440/15290 [02:34<04:35, 35.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5444/15290 [02:34<04:42, 34.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5448/15290 [02:34<04:38, 35.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5452/15290 [02:34<04:36, 35.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5456/15290 [02:35<04:34, 35.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5460/15290 [02:35<04:31, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5464/15290 [02:35<04:29, 36.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5468/15290 [02:35<04:28, 36.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5472/15290 [02:35<04:27, 36.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5476/15290 [02:35<04:30, 36.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5480/15290 [02:35<04:37, 35.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5484/15290 [02:35<04:33, 35.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5488/15290 [02:36<06:21, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5491/15290 [02:36<06:38, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5494/15290 [02:36<07:02, 23.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5497/15290 [02:36<06:45, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5501/15290 [02:36<06:03, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5505/15290 [02:36<05:30, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5509/15290 [02:36<05:12, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5513/15290 [02:36<05:01, 32.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5517/15290 [02:36<04:54, 33.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5521/15290 [02:37<04:48, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5525/15290 [02:37<04:45, 34.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5529/15290 [02:37<04:36, 35.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5533/15290 [02:37<04:35, 35.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5537/15290 [02:37<04:30, 35.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▌ | 5541/15290 [02:37<05:11, 31.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5545/15290 [02:37<05:22, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5549/15290 [02:37<05:10, 31.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5553/15290 [02:38<04:58, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5557/15290 [02:38<04:47, 33.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5561/15290 [02:38<05:00, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5565/15290 [02:38<05:08, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5569/15290 [02:38<04:58, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5573/15290 [02:38<04:49, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
36%|███▋ | 5577/15290 [02:38<04:42, 34.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5581/15290 [02:38<04:36, 35.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5585/15290 [02:39<04:32, 35.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5589/15290 [02:39<04:30, 35.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5593/15290 [02:39<04:30, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5597/15290 [02:39<04:33, 35.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5601/15290 [02:39<04:31, 35.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5605/15290 [02:39<04:25, 36.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5609/15290 [02:39<04:22, 36.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5613/15290 [02:39<04:28, 36.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5617/15290 [02:39<04:40, 34.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5621/15290 [02:40<04:40, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5625/15290 [02:40<04:45, 33.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5629/15290 [02:40<05:17, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5633/15290 [02:40<05:05, 31.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5637/15290 [02:40<05:26, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5641/15290 [02:40<05:38, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5644/15290 [02:40<05:48, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5647/15290 [02:40<05:50, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5651/15290 [02:41<05:37, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5655/15290 [02:41<05:27, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5659/15290 [02:41<05:16, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5663/15290 [02:41<05:14, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5667/15290 [02:41<05:09, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5671/15290 [02:41<05:00, 32.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5675/15290 [02:41<04:59, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5679/15290 [02:41<04:54, 32.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5683/15290 [02:42<04:58, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5687/15290 [02:42<04:52, 32.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5691/15290 [02:42<04:52, 32.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5695/15290 [02:42<04:54, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5699/15290 [02:42<04:58, 32.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5703/15290 [02:42<05:02, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5707/15290 [02:42<05:05, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5711/15290 [02:42<05:09, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5715/15290 [02:43<05:05, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5719/15290 [02:43<05:03, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5723/15290 [02:43<04:57, 32.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5727/15290 [02:43<04:56, 32.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
37%|███▋ | 5731/15290 [02:43<04:58, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5735/15290 [02:43<04:58, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5739/15290 [02:43<05:11, 30.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5743/15290 [02:43<05:08, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5747/15290 [02:44<05:06, 31.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5751/15290 [02:44<05:23, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5754/15290 [02:44<05:22, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5758/15290 [02:44<05:15, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5762/15290 [02:44<05:12, 30.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5766/15290 [02:44<05:08, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5770/15290 [02:44<04:59, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5774/15290 [02:44<04:59, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5778/15290 [02:45<04:52, 32.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5782/15290 [02:45<04:46, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5786/15290 [02:45<04:43, 33.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5790/15290 [02:45<04:39, 33.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5794/15290 [02:45<04:50, 32.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5798/15290 [02:45<05:14, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5802/15290 [02:45<05:18, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5806/15290 [02:46<05:16, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5810/15290 [02:46<05:25, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5814/15290 [02:46<05:19, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5817/15290 [02:46<05:18, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5821/15290 [02:46<05:20, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5824/15290 [02:46<05:33, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5827/15290 [02:46<05:33, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5830/15290 [02:46<05:32, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5833/15290 [02:46<05:30, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5836/15290 [02:47<05:33, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5839/15290 [02:47<05:29, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5842/15290 [02:47<05:28, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5845/15290 [02:47<05:25, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5849/15290 [02:47<05:14, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5853/15290 [02:47<05:14, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5856/15290 [02:47<05:36, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5859/15290 [02:47<05:34, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5863/15290 [02:47<05:24, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5867/15290 [02:48<05:19, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5870/15290 [02:48<05:18, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5873/15290 [02:48<05:18, 29.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5877/15290 [02:48<05:16, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5880/15290 [02:48<05:18, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
38%|███▊ | 5884/15290 [02:48<05:12, 30.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5887/15290 [02:48<05:13, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5891/15290 [02:48<05:00, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5895/15290 [02:49<04:57, 31.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5899/15290 [02:49<04:50, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5903/15290 [02:49<04:52, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5907/15290 [02:49<04:57, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5911/15290 [02:49<04:57, 31.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5915/15290 [02:49<04:54, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5919/15290 [02:49<04:58, 31.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▊ | 5923/15290 [02:49<05:02, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5927/15290 [02:50<05:02, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5931/15290 [02:50<05:07, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5935/15290 [02:50<04:59, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5939/15290 [02:50<04:50, 32.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5943/15290 [02:50<04:47, 32.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5947/15290 [02:50<04:47, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5951/15290 [02:50<04:47, 32.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5955/15290 [02:50<04:50, 32.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5959/15290 [02:51<04:49, 32.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5963/15290 [02:51<04:53, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5967/15290 [02:51<04:48, 32.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5971/15290 [02:51<04:49, 32.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5975/15290 [02:51<04:45, 32.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5979/15290 [02:51<04:45, 32.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5983/15290 [02:51<04:47, 32.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5987/15290 [02:51<04:49, 32.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5991/15290 [02:52<04:56, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5995/15290 [02:52<04:55, 31.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 5999/15290 [02:52<04:59, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6003/15290 [02:52<04:55, 31.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6007/15290 [02:52<04:54, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6011/15290 [02:52<04:56, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6015/15290 [02:52<04:45, 32.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6019/15290 [02:52<04:39, 33.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6023/15290 [02:53<04:37, 33.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6027/15290 [02:53<04:34, 33.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6031/15290 [02:53<04:36, 33.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6035/15290 [02:53<04:32, 33.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
39%|███▉ | 6039/15290 [02:53<04:35, 33.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6043/15290 [02:53<04:32, 33.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6047/15290 [02:53<04:27, 34.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6051/15290 [02:53<04:26, 34.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6055/15290 [02:53<04:26, 34.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6059/15290 [02:54<04:25, 34.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6063/15290 [02:54<04:22, 35.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6067/15290 [02:54<04:21, 35.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6071/15290 [02:54<04:20, 35.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6075/15290 [02:54<04:23, 34.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6079/15290 [02:54<04:21, 35.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6083/15290 [02:54<04:31, 33.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6087/15290 [02:54<04:29, 34.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6091/15290 [02:54<04:31, 33.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6095/15290 [02:55<04:29, 34.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6099/15290 [02:55<04:36, 33.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6103/15290 [02:55<04:40, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6107/15290 [02:55<04:42, 32.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6111/15290 [02:55<04:49, 31.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|███▉ | 6115/15290 [02:55<04:47, 31.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6119/15290 [02:55<04:55, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6123/15290 [02:56<04:54, 31.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6127/15290 [02:56<04:57, 30.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6131/15290 [02:56<04:54, 31.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6135/15290 [02:56<04:50, 31.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6139/15290 [02:56<04:55, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6143/15290 [02:56<04:53, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6147/15290 [02:56<05:02, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6151/15290 [02:56<05:03, 30.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6155/15290 [02:57<04:57, 30.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6159/15290 [02:57<04:50, 31.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6163/15290 [02:57<04:52, 31.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6167/15290 [02:57<04:49, 31.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6171/15290 [02:57<04:42, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6175/15290 [02:57<04:44, 32.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6179/15290 [02:57<05:06, 29.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6183/15290 [02:57<05:15, 28.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6186/15290 [02:58<05:33, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
40%|████ | 6189/15290 [02:58<05:44, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6193/15290 [02:58<05:22, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6197/15290 [02:58<04:58, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6201/15290 [02:58<05:07, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6204/15290 [02:58<05:17, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6207/15290 [02:58<06:06, 24.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6211/15290 [02:59<05:40, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6215/15290 [02:59<05:17, 28.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6219/15290 [02:59<05:05, 29.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6223/15290 [02:59<05:19, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6226/15290 [02:59<05:52, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6230/15290 [02:59<05:24, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6233/15290 [02:59<05:25, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6236/15290 [02:59<05:29, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6239/15290 [03:00<05:23, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6242/15290 [03:00<05:32, 27.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6246/15290 [03:00<05:11, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6250/15290 [03:00<04:59, 30.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6254/15290 [03:00<05:21, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6258/15290 [03:00<05:11, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6261/15290 [03:00<05:11, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6264/15290 [03:00<05:11, 28.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6267/15290 [03:00<05:11, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6270/15290 [03:01<05:20, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6273/15290 [03:01<05:35, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6277/15290 [03:01<05:20, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6280/15290 [03:01<05:27, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6283/15290 [03:01<05:38, 26.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6286/15290 [03:01<05:53, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6289/15290 [03:01<05:41, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6292/15290 [03:01<05:44, 26.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6295/15290 [03:02<05:41, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6299/15290 [03:02<05:12, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6303/15290 [03:02<04:54, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████ | 6307/15290 [03:02<04:55, 30.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6311/15290 [03:02<04:53, 30.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6315/15290 [03:02<04:57, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6319/15290 [03:02<04:58, 30.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6323/15290 [03:02<05:05, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6326/15290 [03:03<05:28, 27.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6330/15290 [03:03<05:17, 28.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6334/15290 [03:03<05:03, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6338/15290 [03:03<04:56, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
41%|████▏ | 6342/15290 [03:03<04:53, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6346/15290 [03:03<04:59, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6350/15290 [03:03<04:52, 30.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6354/15290 [03:03<04:49, 30.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6358/15290 [03:04<04:50, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6362/15290 [03:04<04:45, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6366/15290 [03:04<04:40, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6370/15290 [03:04<04:44, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6374/15290 [03:04<04:41, 31.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6378/15290 [03:04<04:44, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6382/15290 [03:04<05:01, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6386/15290 [03:05<04:53, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6390/15290 [03:05<04:51, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6394/15290 [03:05<04:55, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6398/15290 [03:05<04:45, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6402/15290 [03:05<04:45, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6406/15290 [03:05<04:43, 31.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6410/15290 [03:05<04:45, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6414/15290 [03:05<04:46, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6418/15290 [03:06<04:50, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6422/15290 [03:06<04:57, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6425/15290 [03:06<05:02, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6429/15290 [03:06<04:49, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6433/15290 [03:06<04:39, 31.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6437/15290 [03:06<04:31, 32.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6441/15290 [03:06<04:26, 33.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6445/15290 [03:06<04:28, 32.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6449/15290 [03:06<04:21, 33.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6453/15290 [03:07<04:25, 33.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6457/15290 [03:07<04:23, 33.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6461/15290 [03:07<04:31, 32.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6465/15290 [03:07<04:31, 32.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6469/15290 [03:07<04:36, 31.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6473/15290 [03:07<04:39, 31.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6477/15290 [03:07<04:53, 30.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6481/15290 [03:08<04:53, 30.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6485/15290 [03:08<04:50, 30.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6489/15290 [03:08<04:53, 30.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6493/15290 [03:08<04:55, 29.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
42%|████▏ | 6496/15290 [03:08<04:58, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6499/15290 [03:08<04:59, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6502/15290 [03:08<05:00, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6505/15290 [03:08<04:59, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6509/15290 [03:08<04:50, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6513/15290 [03:09<05:33, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6516/15290 [03:09<05:48, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6520/15290 [03:09<05:17, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6524/15290 [03:09<04:51, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6528/15290 [03:09<04:36, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6532/15290 [03:09<04:27, 32.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6536/15290 [03:09<04:26, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6540/15290 [03:10<04:31, 32.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6544/15290 [03:10<04:46, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6548/15290 [03:10<05:07, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6551/15290 [03:10<05:18, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6555/15290 [03:10<05:02, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6559/15290 [03:10<05:00, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6562/15290 [03:10<05:00, 29.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6566/15290 [03:10<04:49, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6570/15290 [03:11<04:39, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6574/15290 [03:11<04:33, 31.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6578/15290 [03:11<04:31, 32.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6582/15290 [03:11<04:24, 32.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6586/15290 [03:11<04:19, 33.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6590/15290 [03:11<04:20, 33.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6594/15290 [03:11<04:12, 34.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6598/15290 [03:11<04:09, 34.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6602/15290 [03:11<04:17, 33.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6606/15290 [03:12<04:22, 33.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6610/15290 [03:12<04:24, 32.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6614/15290 [03:12<05:02, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6617/15290 [03:12<05:10, 27.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6621/15290 [03:12<04:51, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6625/15290 [03:12<04:44, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6629/15290 [03:12<05:30, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6633/15290 [03:13<05:09, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6637/15290 [03:13<04:50, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6641/15290 [03:13<04:37, 31.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6645/15290 [03:13<04:33, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
43%|████▎ | 6649/15290 [03:13<05:32, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6652/15290 [03:13<05:23, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6655/15290 [03:13<05:31, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6658/15290 [03:13<05:24, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6662/15290 [03:14<04:57, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6665/15290 [03:14<04:55, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6668/15290 [03:14<05:18, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6671/15290 [03:14<05:14, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6675/15290 [03:14<04:54, 29.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6679/15290 [03:14<04:52, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6682/15290 [03:14<05:19, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▎ | 6686/15290 [03:14<05:08, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6690/15290 [03:15<04:50, 29.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6694/15290 [03:15<04:36, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6698/15290 [03:15<04:28, 32.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6702/15290 [03:15<04:20, 32.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6706/15290 [03:15<04:13, 33.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6710/15290 [03:15<04:17, 33.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6714/15290 [03:15<04:24, 32.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6718/15290 [03:15<04:37, 30.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6722/15290 [03:16<04:31, 31.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6726/15290 [03:16<04:28, 31.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6730/15290 [03:16<04:38, 30.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6734/15290 [03:16<04:42, 30.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6738/15290 [03:16<05:30, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6741/15290 [03:16<05:29, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6745/15290 [03:16<05:21, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6748/15290 [03:17<05:23, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6751/15290 [03:17<05:14, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6754/15290 [03:17<05:08, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6758/15290 [03:17<04:55, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6761/15290 [03:17<04:52, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6764/15290 [03:17<04:57, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6767/15290 [03:17<05:31, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6770/15290 [03:17<05:23, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6774/15290 [03:17<04:55, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6777/15290 [03:18<04:54, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6781/15290 [03:18<04:42, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6785/15290 [03:18<05:10, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6788/15290 [03:18<05:21, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6792/15290 [03:18<05:05, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6796/15290 [03:18<04:50, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6800/15290 [03:18<04:43, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
44%|████▍ | 6804/15290 [03:18<04:36, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6808/15290 [03:19<04:33, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6812/15290 [03:19<04:27, 31.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6816/15290 [03:19<04:26, 31.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6820/15290 [03:19<04:27, 31.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6824/15290 [03:19<04:23, 32.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6828/15290 [03:19<04:17, 32.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6832/15290 [03:19<04:21, 32.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6836/15290 [03:19<04:44, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6840/15290 [03:20<04:58, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6843/15290 [03:20<05:19, 26.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6846/15290 [03:20<05:36, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6849/15290 [03:20<05:22, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6853/15290 [03:20<05:01, 28.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6856/15290 [03:20<05:12, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6859/15290 [03:20<06:13, 22.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6863/15290 [03:21<05:37, 25.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6867/15290 [03:21<05:16, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6870/15290 [03:21<05:12, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6873/15290 [03:21<05:13, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▍ | 6877/15290 [03:21<05:01, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6881/15290 [03:21<04:43, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6884/15290 [03:21<05:01, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6887/15290 [03:21<05:24, 25.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6890/15290 [03:22<05:12, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6893/15290 [03:22<05:31, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6896/15290 [03:22<05:34, 25.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6899/15290 [03:22<05:18, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6903/15290 [03:22<04:55, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6907/15290 [03:22<04:44, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6911/15290 [03:22<04:29, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6915/15290 [03:22<04:23, 31.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6919/15290 [03:23<04:40, 29.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6923/15290 [03:23<04:46, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6927/15290 [03:23<04:48, 29.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6930/15290 [03:23<04:57, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6934/15290 [03:23<04:47, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6937/15290 [03:23<04:47, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6940/15290 [03:23<05:05, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6943/15290 [03:23<04:59, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6947/15290 [03:24<04:53, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6950/15290 [03:24<05:01, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
45%|████▌ | 6953/15290 [03:24<04:55, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6957/15290 [03:24<04:38, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6961/15290 [03:24<04:27, 31.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6965/15290 [03:24<04:22, 31.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6969/15290 [03:24<04:24, 31.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6973/15290 [03:24<05:05, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6976/15290 [03:25<05:00, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6980/15290 [03:25<04:43, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6984/15290 [03:25<04:39, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6988/15290 [03:25<04:33, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6992/15290 [03:25<05:47, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6995/15290 [03:25<06:57, 19.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 6998/15290 [03:26<06:35, 20.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7001/15290 [03:26<06:10, 22.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7005/15290 [03:26<05:28, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7009/15290 [03:26<05:07, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7012/15290 [03:26<05:33, 24.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7015/15290 [03:26<05:29, 25.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7018/15290 [03:26<05:28, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7021/15290 [03:26<05:36, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7024/15290 [03:26<05:19, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7027/15290 [03:27<05:15, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7031/15290 [03:27<04:57, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7034/15290 [03:27<05:00, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7037/15290 [03:27<04:54, 28.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7041/15290 [03:27<04:50, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7044/15290 [03:27<04:51, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7048/15290 [03:27<04:33, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7052/15290 [03:27<04:38, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7055/15290 [03:28<04:50, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7058/15290 [03:28<04:50, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7062/15290 [03:28<04:34, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7066/15290 [03:28<04:46, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▌ | 7069/15290 [03:28<04:54, 27.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7073/15290 [03:28<04:42, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7077/15290 [03:28<04:27, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7081/15290 [03:28<04:20, 31.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7085/15290 [03:29<04:25, 30.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7089/15290 [03:29<04:24, 30.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7093/15290 [03:29<04:22, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7097/15290 [03:29<04:39, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7100/15290 [03:29<04:48, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7104/15290 [03:29<04:40, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
46%|████▋ | 7108/15290 [03:29<04:39, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7112/15290 [03:29<04:35, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7115/15290 [03:30<04:50, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7118/15290 [03:30<04:56, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7121/15290 [03:30<04:59, 27.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7125/15290 [03:30<04:45, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7128/15290 [03:30<04:53, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7131/15290 [03:30<04:52, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7135/15290 [03:30<04:38, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7139/15290 [03:30<04:32, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7143/15290 [03:31<04:22, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7147/15290 [03:31<04:26, 30.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7151/15290 [03:31<04:18, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7155/15290 [03:31<04:12, 32.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7159/15290 [03:31<04:07, 32.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7163/15290 [03:31<04:11, 32.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7167/15290 [03:31<04:13, 32.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7171/15290 [03:31<04:28, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7175/15290 [03:32<04:30, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7179/15290 [03:32<04:37, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7182/15290 [03:32<04:38, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7186/15290 [03:32<04:30, 29.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7190/15290 [03:32<04:28, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7194/15290 [03:32<04:23, 30.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7198/15290 [03:32<04:27, 30.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7202/15290 [03:32<04:29, 30.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7206/15290 [03:33<04:32, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7209/15290 [03:33<04:55, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7212/15290 [03:33<04:55, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7215/15290 [03:33<05:07, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7218/15290 [03:33<05:13, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7221/15290 [03:33<05:08, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7224/15290 [03:33<05:10, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7227/15290 [03:33<05:08, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7231/15290 [03:34<04:44, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7235/15290 [03:34<04:31, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7238/15290 [03:34<04:44, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7241/15290 [03:34<04:57, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7244/15290 [03:34<05:05, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7247/15290 [03:34<05:09, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7251/15290 [03:34<04:47, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7255/15290 [03:34<04:32, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
47%|████▋ | 7259/15290 [03:35<04:19, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7263/15290 [03:35<04:35, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7266/15290 [03:35<04:51, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7269/15290 [03:35<04:53, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7273/15290 [03:35<04:37, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7276/15290 [03:35<04:39, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7279/15290 [03:35<04:36, 29.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7282/15290 [03:35<04:37, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7286/15290 [03:35<04:30, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7290/15290 [03:36<04:25, 30.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7294/15290 [03:36<04:20, 30.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7298/15290 [03:36<04:17, 31.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7302/15290 [03:36<04:07, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7306/15290 [03:36<04:41, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7309/15290 [03:36<04:54, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7312/15290 [03:36<05:01, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7315/15290 [03:37<05:03, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7318/15290 [03:37<04:55, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7322/15290 [03:37<04:47, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7326/15290 [03:37<04:29, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7330/15290 [03:37<04:19, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7334/15290 [03:37<04:29, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7337/15290 [03:37<04:39, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7340/15290 [03:37<04:39, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7343/15290 [03:37<04:52, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7346/15290 [03:38<04:54, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7349/15290 [03:38<04:46, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7352/15290 [03:38<04:54, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7355/15290 [03:38<04:50, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7358/15290 [03:38<04:54, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7361/15290 [03:38<04:54, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7365/15290 [03:38<04:37, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7368/15290 [03:38<04:36, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7371/15290 [03:38<04:37, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7375/15290 [03:39<04:28, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7379/15290 [03:39<04:14, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7383/15290 [03:39<04:04, 32.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7387/15290 [03:39<03:56, 33.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7391/15290 [03:39<03:55, 33.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7395/15290 [03:39<04:11, 31.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7399/15290 [03:39<04:09, 31.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7403/15290 [03:39<04:25, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7407/15290 [03:40<04:20, 30.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7411/15290 [03:40<04:32, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
48%|████▊ | 7415/15290 [03:40<04:28, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7418/15290 [03:40<04:37, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7421/15290 [03:40<04:40, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7424/15290 [03:40<04:35, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7427/15290 [03:40<04:41, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7431/15290 [03:40<04:30, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7434/15290 [03:41<04:31, 28.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7437/15290 [03:41<04:42, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7441/15290 [03:41<04:29, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7444/15290 [03:41<04:39, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7447/15290 [03:41<04:34, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▊ | 7451/15290 [03:41<04:14, 30.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7455/15290 [03:41<04:12, 31.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7459/15290 [03:41<04:11, 31.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7463/15290 [03:42<04:02, 32.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7467/15290 [03:42<03:58, 32.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7471/15290 [03:42<04:26, 29.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7475/15290 [03:42<04:31, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7479/15290 [03:42<04:28, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7482/15290 [03:42<04:29, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7486/15290 [03:42<04:24, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7490/15290 [03:42<04:17, 30.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7494/15290 [03:43<04:31, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7498/15290 [03:43<04:24, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7501/15290 [03:43<04:35, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7504/15290 [03:43<04:39, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7508/15290 [03:43<04:24, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7511/15290 [03:43<04:27, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7514/15290 [03:43<04:34, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7518/15290 [03:43<04:23, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7521/15290 [03:44<04:29, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7524/15290 [03:44<04:32, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7528/15290 [03:44<04:17, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7532/15290 [03:44<04:31, 28.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7536/15290 [03:44<04:24, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7540/15290 [03:44<04:21, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7543/15290 [03:44<04:26, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7547/15290 [03:44<04:16, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7551/15290 [03:45<04:07, 31.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7555/15290 [03:45<03:58, 32.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7559/15290 [03:45<04:04, 31.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7563/15290 [03:45<04:02, 31.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
49%|████▉ | 7567/15290 [03:45<03:59, 32.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7571/15290 [03:45<03:58, 32.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7575/15290 [03:45<04:17, 29.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7579/15290 [03:45<04:42, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7583/15290 [03:46<04:33, 28.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7586/15290 [03:46<04:37, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7589/15290 [03:46<04:32, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7593/15290 [03:46<04:16, 30.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7597/15290 [03:46<04:21, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7600/15290 [03:46<04:21, 29.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7603/15290 [03:46<04:23, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7607/15290 [03:46<04:12, 30.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7611/15290 [03:47<04:14, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7615/15290 [03:47<04:22, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7618/15290 [03:47<04:20, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7622/15290 [03:47<04:11, 30.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7626/15290 [03:47<04:23, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7630/15290 [03:47<04:16, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7634/15290 [03:47<04:35, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7637/15290 [03:47<04:40, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7641/15290 [03:48<04:34, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|████▉ | 7644/15290 [03:48<04:44, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7648/15290 [03:48<04:29, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7651/15290 [03:48<04:36, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7654/15290 [03:48<04:43, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7658/15290 [03:48<04:26, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7661/15290 [03:48<04:39, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7664/15290 [03:48<04:35, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7667/15290 [03:49<04:35, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7670/15290 [03:49<04:50, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7673/15290 [03:49<04:50, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7677/15290 [03:49<04:39, 27.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7680/15290 [03:49<04:46, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7683/15290 [03:49<04:40, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7687/15290 [03:49<04:23, 28.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7690/15290 [03:49<04:41, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7693/15290 [03:50<04:44, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7697/15290 [03:50<04:26, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7700/15290 [03:50<04:38, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7703/15290 [03:50<04:39, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7707/15290 [03:50<04:28, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7710/15290 [03:50<04:40, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7714/15290 [03:50<04:23, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7717/15290 [03:50<04:28, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
50%|█████ | 7720/15290 [03:50<04:38, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7723/15290 [03:51<04:45, 26.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7726/15290 [03:51<04:54, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7730/15290 [03:51<04:31, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7734/15290 [03:51<04:26, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7737/15290 [03:51<04:26, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7741/15290 [03:51<04:16, 29.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7744/15290 [03:51<04:29, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7747/15290 [03:51<04:26, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7750/15290 [03:52<04:25, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7753/15290 [03:52<04:35, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7756/15290 [03:52<04:29, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7759/15290 [03:52<04:24, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7762/15290 [03:52<04:40, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7765/15290 [03:52<04:36, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7768/15290 [03:52<04:46, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7771/15290 [03:52<04:50, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7774/15290 [03:52<04:46, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7778/15290 [03:53<04:28, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7781/15290 [03:53<04:41, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7784/15290 [03:53<04:43, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7788/15290 [03:53<04:26, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7792/15290 [03:53<04:20, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7795/15290 [03:53<04:19, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7798/15290 [03:53<04:28, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7801/15290 [03:53<04:31, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7805/15290 [03:54<04:13, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7809/15290 [03:54<04:08, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7813/15290 [03:54<04:13, 29.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7817/15290 [03:54<04:06, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7821/15290 [03:54<04:08, 30.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7825/15290 [03:54<04:30, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7828/15290 [03:54<04:27, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7831/15290 [03:54<04:33, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████ | 7834/15290 [03:55<04:29, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7838/15290 [03:55<04:23, 28.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7841/15290 [03:55<04:32, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7844/15290 [03:55<04:30, 27.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7848/15290 [03:55<04:16, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7851/15290 [03:55<04:25, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7855/15290 [03:55<04:15, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7858/15290 [03:55<04:15, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7861/15290 [03:56<04:19, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7865/15290 [03:56<04:06, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7869/15290 [03:56<04:02, 30.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
51%|█████▏ | 7873/15290 [03:56<04:09, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7877/15290 [03:56<03:58, 31.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7881/15290 [03:56<04:14, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7884/15290 [03:56<04:15, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7888/15290 [03:56<04:06, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7892/15290 [03:57<03:56, 31.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7896/15290 [03:57<03:56, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7900/15290 [03:57<03:53, 31.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7904/15290 [03:57<04:20, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7907/15290 [03:57<04:22, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7911/15290 [03:57<04:09, 29.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7915/15290 [03:57<04:14, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7918/15290 [03:57<04:21, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7922/15290 [03:58<04:11, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7926/15290 [03:58<04:05, 30.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7930/15290 [03:58<04:11, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7933/15290 [03:58<04:15, 28.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7937/15290 [03:58<04:06, 29.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7941/15290 [03:58<03:56, 31.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7945/15290 [03:58<04:06, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7949/15290 [03:58<04:12, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7952/15290 [03:59<04:10, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7955/15290 [03:59<04:15, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7958/15290 [03:59<04:16, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7962/15290 [03:59<04:02, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7966/15290 [03:59<04:14, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7969/15290 [03:59<04:27, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7973/15290 [03:59<04:12, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7976/15290 [03:59<04:10, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7979/15290 [04:00<04:18, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7982/15290 [04:00<04:20, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7985/15290 [04:00<04:16, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7988/15290 [04:00<04:14, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7991/15290 [04:00<04:13, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7995/15290 [04:00<04:02, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 7999/15290 [04:00<03:56, 30.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8003/15290 [04:00<04:12, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8007/15290 [04:00<04:03, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8011/15290 [04:01<04:04, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8014/15290 [04:01<04:08, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8018/15290 [04:01<03:54, 31.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8022/15290 [04:01<04:14, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
52%|█████▏ | 8026/15290 [04:01<04:07, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8030/15290 [04:01<04:02, 29.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8034/15290 [04:01<03:53, 31.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8038/15290 [04:01<03:54, 30.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8042/15290 [04:02<04:02, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8046/15290 [04:02<03:59, 30.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8050/15290 [04:02<04:02, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8054/15290 [04:02<03:54, 30.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8058/15290 [04:02<03:56, 30.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8062/15290 [04:02<03:55, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8066/15290 [04:02<04:00, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8070/15290 [04:03<04:18, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8073/15290 [04:03<04:14, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8076/15290 [04:03<04:23, 27.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8079/15290 [04:03<04:22, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8082/15290 [04:03<04:25, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8085/15290 [04:03<04:27, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8089/15290 [04:03<04:11, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8092/15290 [04:03<04:38, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8095/15290 [04:04<04:38, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8098/15290 [04:04<04:46, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8101/15290 [04:04<04:47, 25.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8104/15290 [04:04<04:41, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8107/15290 [04:04<04:43, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8111/15290 [04:04<04:33, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8114/15290 [04:04<04:52, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8117/15290 [04:04<04:39, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8120/15290 [04:05<04:41, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8123/15290 [04:05<04:46, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8126/15290 [04:05<05:35, 21.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8129/15290 [04:05<06:45, 17.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8131/15290 [04:05<07:32, 15.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8133/15290 [04:05<08:01, 14.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8136/15290 [04:06<07:30, 15.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8139/15290 [04:06<06:27, 18.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8143/15290 [04:06<05:15, 22.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8147/15290 [04:06<04:30, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8151/15290 [04:06<04:02, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8155/15290 [04:06<04:04, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8159/15290 [04:06<04:03, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8163/15290 [04:06<03:56, 30.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8167/15290 [04:07<04:04, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8171/15290 [04:07<03:54, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8175/15290 [04:07<03:48, 31.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
53%|█████▎ | 8179/15290 [04:07<04:05, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8182/15290 [04:07<04:03, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8186/15290 [04:07<03:46, 31.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8190/15290 [04:07<03:37, 32.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8194/15290 [04:07<03:32, 33.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8198/15290 [04:08<03:49, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8202/15290 [04:08<03:59, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8206/15290 [04:08<04:01, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8209/15290 [04:08<04:18, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8212/15290 [04:08<04:21, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8215/15290 [04:08<04:27, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▎ | 8218/15290 [04:08<04:33, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8221/15290 [04:08<04:29, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8225/15290 [04:09<04:12, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8228/15290 [04:09<04:19, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8231/15290 [04:09<04:21, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8235/15290 [04:09<04:06, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8238/15290 [04:09<04:12, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8241/15290 [04:09<04:15, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8244/15290 [04:09<04:12, 27.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8248/15290 [04:09<04:03, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8252/15290 [04:09<03:54, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8256/15290 [04:10<03:45, 31.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8260/15290 [04:10<03:51, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8264/15290 [04:10<03:49, 30.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8268/15290 [04:10<03:59, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8271/15290 [04:10<04:17, 27.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8274/15290 [04:10<04:21, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8277/15290 [04:10<04:46, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8280/15290 [04:11<04:53, 23.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8283/15290 [04:11<04:39, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8286/15290 [04:11<04:39, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8290/15290 [04:11<04:19, 27.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8294/15290 [04:11<03:51, 30.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8298/15290 [04:11<03:34, 32.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8302/15290 [04:11<03:28, 33.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8306/15290 [04:11<04:04, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8310/15290 [04:12<03:55, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8314/15290 [04:12<03:53, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8318/15290 [04:12<03:50, 30.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8322/15290 [04:12<03:51, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8326/15290 [04:12<04:03, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8329/15290 [04:12<04:03, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
54%|█████▍ | 8333/15290 [04:12<03:51, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8337/15290 [04:12<03:45, 30.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8341/15290 [04:13<03:45, 30.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8345/15290 [04:13<04:12, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8348/15290 [04:13<04:12, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8352/15290 [04:13<04:00, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8356/15290 [04:13<03:48, 30.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8360/15290 [04:13<04:05, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8363/15290 [04:13<04:01, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8367/15290 [04:13<03:49, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8371/15290 [04:14<03:48, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8375/15290 [04:14<04:08, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8379/15290 [04:14<04:01, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8383/15290 [04:14<03:49, 30.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8387/15290 [04:14<03:50, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8391/15290 [04:14<04:03, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8394/15290 [04:14<04:13, 27.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8397/15290 [04:15<04:07, 27.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8401/15290 [04:15<03:55, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8404/15290 [04:15<04:04, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▍ | 8407/15290 [04:15<04:05, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8410/15290 [04:15<04:01, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8414/15290 [04:15<03:50, 29.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8418/15290 [04:15<03:52, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8421/15290 [04:15<04:15, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8425/15290 [04:15<04:01, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8429/15290 [04:16<03:51, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8432/15290 [04:16<04:01, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8435/15290 [04:16<04:05, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8439/15290 [04:16<03:50, 29.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8443/15290 [04:16<03:39, 31.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8447/15290 [04:16<03:34, 31.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8451/15290 [04:16<03:31, 32.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8455/15290 [04:16<03:25, 33.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8459/15290 [04:17<03:37, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8463/15290 [04:17<04:08, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8466/15290 [04:17<04:04, 27.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8470/15290 [04:17<03:53, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8473/15290 [04:17<03:56, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8477/15290 [04:17<03:53, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8481/15290 [04:17<03:43, 30.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
55%|█████▌ | 8485/15290 [04:17<03:38, 31.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8489/15290 [04:18<03:36, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8493/15290 [04:18<03:32, 31.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8497/15290 [04:18<03:34, 31.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8501/15290 [04:18<03:36, 31.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8505/15290 [04:18<03:36, 31.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8509/15290 [04:18<03:49, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8512/15290 [04:18<03:52, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8516/15290 [04:18<03:47, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8520/15290 [04:19<03:42, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8524/15290 [04:19<03:45, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8528/15290 [04:19<03:43, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8532/15290 [04:19<03:45, 29.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8536/15290 [04:19<03:44, 30.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8540/15290 [04:19<03:46, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8543/15290 [04:19<03:56, 28.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8546/15290 [04:20<03:53, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8550/15290 [04:20<03:45, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8554/15290 [04:20<03:42, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8558/15290 [04:20<03:40, 30.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8562/15290 [04:20<03:34, 31.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8566/15290 [04:20<03:31, 31.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8570/15290 [04:20<03:32, 31.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8574/15290 [04:20<03:36, 30.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8578/15290 [04:21<03:41, 30.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8582/15290 [04:21<03:50, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8585/15290 [04:21<03:57, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8588/15290 [04:21<03:59, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8591/15290 [04:21<03:56, 28.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8595/15290 [04:21<03:52, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▌ | 8598/15290 [04:21<03:57, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8601/15290 [04:21<03:59, 27.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8604/15290 [04:21<04:00, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8607/15290 [04:22<04:21, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8610/15290 [04:22<04:13, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8613/15290 [04:22<04:07, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8616/15290 [04:22<04:19, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8619/15290 [04:22<04:22, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8622/15290 [04:22<04:38, 23.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8625/15290 [04:22<04:31, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8628/15290 [04:22<04:41, 23.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8631/15290 [04:23<04:48, 23.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8634/15290 [04:23<04:34, 24.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
56%|█████▋ | 8637/15290 [04:23<04:23, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8640/15290 [04:23<04:16, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8644/15290 [04:23<03:59, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8647/15290 [04:23<03:58, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8651/15290 [04:23<03:48, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8654/15290 [04:23<03:47, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8658/15290 [04:24<03:41, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8662/15290 [04:24<03:42, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8666/15290 [04:24<03:39, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8670/15290 [04:24<03:38, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8674/15290 [04:24<03:37, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8678/15290 [04:24<03:40, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8681/15290 [04:24<03:48, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8684/15290 [04:24<03:47, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8687/15290 [04:25<03:46, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8690/15290 [04:25<03:47, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8693/15290 [04:25<03:45, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8696/15290 [04:25<03:47, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8699/15290 [04:25<03:48, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8703/15290 [04:25<03:44, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8706/15290 [04:25<03:44, 29.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8709/15290 [04:25<03:46, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8712/15290 [04:25<03:55, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8715/15290 [04:26<04:17, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8718/15290 [04:26<04:33, 24.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8721/15290 [04:26<04:23, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8724/15290 [04:26<04:19, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8727/15290 [04:26<04:13, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8730/15290 [04:26<04:03, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8734/15290 [04:26<03:45, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8738/15290 [04:26<03:43, 29.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8741/15290 [04:26<03:56, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8744/15290 [04:27<03:57, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8748/15290 [04:27<03:45, 28.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8752/15290 [04:27<03:47, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8755/15290 [04:27<03:54, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8759/15290 [04:27<03:44, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8763/15290 [04:27<03:39, 29.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8766/15290 [04:27<03:44, 29.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8769/15290 [04:27<03:51, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8772/15290 [04:28<03:57, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8776/15290 [04:28<03:50, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8780/15290 [04:28<03:42, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8784/15290 [04:28<03:32, 30.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8788/15290 [04:28<03:38, 29.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
57%|█████▋ | 8791/15290 [04:28<03:43, 29.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8794/15290 [04:28<03:43, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8797/15290 [04:28<03:50, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8800/15290 [04:29<03:50, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8804/15290 [04:29<03:44, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8807/15290 [04:29<03:49, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8811/15290 [04:29<03:36, 29.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8814/15290 [04:29<03:44, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8817/15290 [04:29<03:42, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8821/15290 [04:29<03:33, 30.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8825/15290 [04:29<03:26, 31.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8829/15290 [04:29<03:28, 31.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8833/15290 [04:30<03:28, 30.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8837/15290 [04:30<03:31, 30.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8841/15290 [04:30<03:37, 29.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8844/15290 [04:30<03:38, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8847/15290 [04:30<03:38, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8850/15290 [04:30<03:39, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8854/15290 [04:30<03:41, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8857/15290 [04:30<03:45, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8860/15290 [04:31<03:43, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8863/15290 [04:31<03:45, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8866/15290 [04:31<03:54, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8869/15290 [04:31<03:53, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8872/15290 [04:31<03:52, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8875/15290 [04:31<03:48, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8878/15290 [04:31<03:46, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8882/15290 [04:31<03:40, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8886/15290 [04:31<03:33, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8889/15290 [04:32<03:37, 29.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8892/15290 [04:32<03:38, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8895/15290 [04:32<03:37, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8898/15290 [04:32<03:36, 29.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8901/15290 [04:32<03:40, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8904/15290 [04:32<03:40, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8907/15290 [04:32<03:41, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8910/15290 [04:32<03:39, 29.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8913/15290 [04:32<03:49, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8916/15290 [04:33<03:52, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8919/15290 [04:33<04:01, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8922/15290 [04:33<03:54, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8926/15290 [04:33<03:43, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8929/15290 [04:33<03:43, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8932/15290 [04:33<03:58, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8935/15290 [04:33<04:47, 22.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8938/15290 [04:33<04:51, 21.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8941/15290 [04:34<04:33, 23.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
58%|█████▊ | 8944/15290 [04:34<04:29, 23.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8947/15290 [04:34<04:38, 22.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8950/15290 [04:34<04:56, 21.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8953/15290 [04:34<04:44, 22.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8956/15290 [04:34<04:33, 23.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8959/15290 [04:34<04:24, 23.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8962/15290 [04:34<04:11, 25.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8965/15290 [04:35<04:11, 25.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8968/15290 [04:35<04:02, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8972/15290 [04:35<03:45, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8976/15290 [04:35<03:39, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▊ | 8979/15290 [04:35<03:41, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 8983/15290 [04:35<03:32, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 8986/15290 [04:35<04:03, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 8989/15290 [04:35<04:35, 22.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 8992/15290 [04:36<04:39, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 8995/15290 [04:36<05:01, 20.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 8998/15290 [04:36<05:11, 20.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9001/15290 [04:36<05:01, 20.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9004/15290 [04:36<05:02, 20.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9007/15290 [04:36<04:35, 22.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9011/15290 [04:36<04:04, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9015/15290 [04:37<03:46, 27.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9018/15290 [04:37<03:47, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9021/15290 [04:37<04:00, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9026/15290 [04:37<03:28, 30.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9030/15290 [04:37<03:26, 30.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9035/15290 [04:37<03:04, 33.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9041/15290 [04:37<02:37, 39.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9046/15290 [04:37<02:34, 40.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9051/15290 [04:38<02:25, 42.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9056/15290 [04:38<02:25, 42.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9062/15290 [04:38<02:17, 45.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9067/15290 [04:38<02:16, 45.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9072/15290 [04:38<02:13, 46.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9078/15290 [04:38<02:07, 48.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9084/15290 [04:38<02:02, 50.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9090/15290 [04:38<01:58, 52.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
59%|█████▉ | 9096/15290 [04:38<02:08, 48.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9101/15290 [04:39<02:19, 44.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9106/15290 [04:39<02:26, 42.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9111/15290 [04:39<02:29, 41.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9116/15290 [04:39<02:46, 37.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9120/15290 [04:39<02:52, 35.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9124/15290 [04:39<02:57, 34.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9128/15290 [04:39<03:15, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9132/15290 [04:40<03:18, 30.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9136/15290 [04:40<03:23, 30.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9140/15290 [04:40<03:26, 29.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9144/15290 [04:40<03:25, 29.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9148/15290 [04:40<03:24, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9152/15290 [04:40<03:32, 28.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9155/15290 [04:40<03:33, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9158/15290 [04:40<03:42, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9161/15290 [04:41<03:42, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9164/15290 [04:41<03:42, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9168/15290 [04:41<03:31, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|█████▉ | 9172/15290 [04:41<03:23, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9176/15290 [04:41<03:18, 30.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9180/15290 [04:41<03:21, 30.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9184/15290 [04:41<03:23, 30.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9188/15290 [04:41<03:27, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9191/15290 [04:42<03:27, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9195/15290 [04:42<03:21, 30.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9199/15290 [04:42<03:24, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9202/15290 [04:42<03:31, 28.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9205/15290 [04:42<03:32, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9209/15290 [04:42<03:25, 29.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9213/15290 [04:42<03:21, 30.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9217/15290 [04:42<03:27, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9220/15290 [04:43<03:31, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9223/15290 [04:43<03:34, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9226/15290 [04:43<03:33, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9229/15290 [04:43<03:47, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9233/15290 [04:43<03:31, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9237/15290 [04:43<03:22, 29.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9240/15290 [04:43<03:37, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9243/15290 [04:43<03:41, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9246/15290 [04:43<03:40, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
60%|██████ | 9249/15290 [04:44<03:38, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9252/15290 [04:44<03:38, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9255/15290 [04:44<03:45, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9258/15290 [04:44<03:54, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9262/15290 [04:44<03:33, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9266/15290 [04:44<03:29, 28.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9269/15290 [04:44<04:02, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9272/15290 [04:45<04:13, 23.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9276/15290 [04:45<03:49, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9280/15290 [04:45<03:37, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9283/15290 [04:45<03:41, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9286/15290 [04:45<03:40, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9290/15290 [04:45<03:25, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9294/15290 [04:45<03:20, 29.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9297/15290 [04:45<03:55, 25.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9300/15290 [04:46<03:47, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9303/15290 [04:46<03:48, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9306/15290 [04:46<03:50, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9310/15290 [04:46<03:35, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9314/15290 [04:46<03:26, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9317/15290 [04:46<03:26, 28.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9320/15290 [04:46<03:47, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9323/15290 [04:46<03:57, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9326/15290 [04:46<03:56, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9329/15290 [04:47<04:07, 24.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9332/15290 [04:47<04:01, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9335/15290 [04:47<03:56, 25.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9338/15290 [04:47<03:48, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9342/15290 [04:47<03:27, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9346/15290 [04:47<03:19, 29.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9349/15290 [04:47<03:39, 27.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9352/15290 [04:47<03:43, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9356/15290 [04:48<03:31, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9360/15290 [04:48<03:29, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████ | 9363/15290 [04:48<03:39, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9366/15290 [04:48<03:36, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9369/15290 [04:48<03:33, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9372/15290 [04:48<03:38, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9375/15290 [04:48<03:35, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9379/15290 [04:48<03:21, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9382/15290 [04:49<03:31, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9385/15290 [04:49<03:39, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9389/15290 [04:49<03:25, 28.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9392/15290 [04:49<03:33, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9395/15290 [04:49<03:32, 27.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9399/15290 [04:49<03:22, 29.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
61%|██████▏ | 9402/15290 [04:49<03:24, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9405/15290 [04:49<03:32, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9408/15290 [04:49<03:34, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9412/15290 [04:50<03:24, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9415/15290 [04:50<03:32, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9418/15290 [04:50<03:29, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9422/15290 [04:50<03:14, 30.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9426/15290 [04:50<03:31, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9429/15290 [04:50<03:35, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9432/15290 [04:50<03:43, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9435/15290 [04:50<03:52, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9438/15290 [04:51<03:43, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9441/15290 [04:51<03:53, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9444/15290 [04:51<03:51, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9447/15290 [04:51<03:46, 25.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9450/15290 [04:51<03:41, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9454/15290 [04:51<03:31, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9457/15290 [04:51<03:39, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9460/15290 [04:51<03:45, 25.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9463/15290 [04:52<03:42, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9466/15290 [04:52<03:43, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9469/15290 [04:52<03:47, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9472/15290 [04:52<03:49, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9476/15290 [04:52<03:33, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9479/15290 [04:52<03:41, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9482/15290 [04:52<03:41, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9485/15290 [04:52<03:50, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9488/15290 [04:53<03:47, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9491/15290 [04:53<03:39, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9494/15290 [04:53<03:37, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9497/15290 [04:53<03:40, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9500/15290 [04:53<03:35, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9503/15290 [04:53<03:45, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9506/15290 [04:53<03:50, 25.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9509/15290 [04:53<03:45, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9512/15290 [04:53<03:37, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9515/15290 [04:54<03:38, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9518/15290 [04:54<03:33, 27.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9521/15290 [04:54<03:28, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9524/15290 [04:54<03:38, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9527/15290 [04:54<03:42, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9530/15290 [04:54<03:37, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9533/15290 [04:54<03:34, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9537/15290 [04:54<03:23, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9540/15290 [04:54<03:24, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9543/15290 [04:55<03:27, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9547/15290 [04:55<03:19, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9550/15290 [04:55<03:22, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9553/15290 [04:55<03:26, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
62%|██████▏ | 9556/15290 [04:55<03:32, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9559/15290 [04:55<03:28, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9563/15290 [04:55<03:21, 28.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9567/15290 [04:55<03:14, 29.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9570/15290 [04:55<03:16, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9573/15290 [04:56<03:15, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9576/15290 [04:56<03:16, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9580/15290 [04:56<03:09, 30.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9584/15290 [04:56<03:11, 29.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9587/15290 [04:56<03:14, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9591/15290 [04:56<03:10, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9594/15290 [04:56<03:13, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9597/15290 [04:56<03:20, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9600/15290 [04:57<03:21, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9603/15290 [04:57<03:19, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9606/15290 [04:57<03:17, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9609/15290 [04:57<03:20, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9612/15290 [04:57<03:23, 27.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9615/15290 [04:57<03:21, 28.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9618/15290 [04:57<03:32, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9621/15290 [04:57<03:30, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9624/15290 [04:57<03:29, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9627/15290 [04:58<03:35, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9630/15290 [04:58<03:44, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9633/15290 [04:58<03:40, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9636/15290 [04:58<03:38, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9640/15290 [04:58<03:25, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9644/15290 [04:58<03:12, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9648/15290 [04:58<03:04, 30.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9652/15290 [04:58<03:00, 31.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9656/15290 [04:58<03:00, 31.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9660/15290 [04:59<03:03, 30.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9664/15290 [04:59<03:08, 29.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9667/15290 [04:59<03:11, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9670/15290 [04:59<03:11, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9673/15290 [04:59<03:18, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9676/15290 [04:59<03:21, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9679/15290 [04:59<03:23, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9682/15290 [04:59<03:18, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9685/15290 [05:00<03:19, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9688/15290 [05:00<03:19, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9691/15290 [05:00<03:16, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9694/15290 [05:00<03:18, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9697/15290 [05:00<03:23, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9701/15290 [05:00<03:18, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9704/15290 [05:00<03:15, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
63%|██████▎ | 9707/15290 [05:00<03:14, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9710/15290 [05:00<03:18, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9713/15290 [05:01<03:16, 28.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9716/15290 [05:01<03:19, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9719/15290 [05:01<03:16, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9722/15290 [05:01<03:21, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9725/15290 [05:01<03:26, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9728/15290 [05:01<03:22, 27.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9732/15290 [05:01<03:10, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9736/15290 [05:01<03:03, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9740/15290 [05:01<03:02, 30.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▎ | 9744/15290 [05:02<02:56, 31.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9748/15290 [05:02<02:57, 31.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9752/15290 [05:02<03:02, 30.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9756/15290 [05:02<03:15, 28.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9759/15290 [05:02<03:13, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9763/15290 [05:02<03:07, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9766/15290 [05:02<03:07, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9769/15290 [05:02<03:21, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9772/15290 [05:03<03:19, 27.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9775/15290 [05:03<03:18, 27.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9779/15290 [05:03<03:09, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9783/15290 [05:03<03:06, 29.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9787/15290 [05:03<03:03, 30.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9791/15290 [05:03<02:59, 30.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9795/15290 [05:03<02:56, 31.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9799/15290 [05:03<02:56, 31.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9803/15290 [05:04<03:22, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9806/15290 [05:04<03:20, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9809/15290 [05:04<03:16, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9812/15290 [05:04<03:16, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9816/15290 [05:04<03:07, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9820/15290 [05:04<03:03, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9824/15290 [05:04<02:57, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9828/15290 [05:04<02:53, 31.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9832/15290 [05:05<02:59, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9836/15290 [05:05<03:05, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9839/15290 [05:05<03:10, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9842/15290 [05:05<03:12, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9845/15290 [05:05<04:14, 21.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9848/15290 [05:05<04:39, 19.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9851/15290 [05:06<04:54, 18.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9854/15290 [05:06<04:39, 19.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9857/15290 [05:06<04:11, 21.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
64%|██████▍ | 9861/15290 [05:06<03:34, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9865/15290 [05:06<03:19, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9869/15290 [05:06<03:05, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9873/15290 [05:06<02:54, 31.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9877/15290 [05:06<02:56, 30.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9881/15290 [05:07<02:57, 30.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9885/15290 [05:07<02:45, 32.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9889/15290 [05:07<02:43, 32.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9893/15290 [05:07<02:44, 32.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9897/15290 [05:07<02:50, 31.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9901/15290 [05:07<02:59, 30.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9905/15290 [05:07<03:01, 29.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9908/15290 [05:07<03:05, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9911/15290 [05:07<03:07, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9914/15290 [05:08<03:05, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9918/15290 [05:08<03:01, 29.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9922/15290 [05:08<02:57, 30.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9926/15290 [05:08<02:54, 30.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9930/15290 [05:08<02:53, 30.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9934/15290 [05:08<02:57, 30.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▍ | 9938/15290 [05:08<03:03, 29.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9941/15290 [05:08<03:02, 29.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9945/15290 [05:09<02:59, 29.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9949/15290 [05:09<02:57, 30.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9953/15290 [05:09<03:00, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9957/15290 [05:09<03:00, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9960/15290 [05:09<03:03, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9963/15290 [05:09<03:05, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9966/15290 [05:09<03:17, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9969/15290 [05:09<03:18, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9972/15290 [05:10<03:23, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9975/15290 [05:10<03:24, 26.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9978/15290 [05:10<03:23, 26.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9981/15290 [05:10<03:16, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9984/15290 [05:10<03:14, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9987/15290 [05:10<03:16, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9990/15290 [05:10<03:37, 24.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9993/15290 [05:10<03:44, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9996/15290 [05:11<03:40, 24.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 9999/15290 [05:11<03:35, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 10002/15290 [05:11<03:36, 24.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 10005/15290 [05:11<03:36, 24.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 10008/15290 [05:11<03:27, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 10011/15290 [05:11<03:24, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
65%|██████▌ | 10014/15290 [05:11<03:16, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10017/15290 [05:11<03:10, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10020/15290 [05:11<03:09, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10023/15290 [05:12<03:07, 28.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10026/15290 [05:12<03:09, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10029/15290 [05:12<03:12, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10032/15290 [05:12<03:15, 26.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10035/15290 [05:12<03:12, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10038/15290 [05:12<03:12, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10041/15290 [05:12<03:18, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10044/15290 [05:12<03:17, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10047/15290 [05:12<03:14, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10050/15290 [05:13<03:15, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10053/15290 [05:13<03:12, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10056/15290 [05:13<03:16, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10059/15290 [05:13<03:16, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10062/15290 [05:13<03:17, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10065/15290 [05:13<03:18, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10068/15290 [05:13<03:18, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10071/15290 [05:13<03:20, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10074/15290 [05:13<03:24, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10077/15290 [05:14<03:24, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10080/15290 [05:14<03:30, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10083/15290 [05:14<03:27, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10086/15290 [05:14<03:24, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10089/15290 [05:14<03:22, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10092/15290 [05:14<03:16, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10095/15290 [05:14<03:18, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10098/15290 [05:14<03:17, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10101/15290 [05:15<03:11, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10104/15290 [05:15<03:08, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10107/15290 [05:15<03:06, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10110/15290 [05:15<03:03, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10113/15290 [05:15<03:07, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10116/15290 [05:15<03:04, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10119/15290 [05:15<03:01, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10122/15290 [05:15<03:03, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10125/15290 [05:15<03:03, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▌ | 10129/15290 [05:16<02:57, 29.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10132/15290 [05:16<02:57, 29.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10135/15290 [05:16<02:57, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10138/15290 [05:16<02:57, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10141/15290 [05:16<02:56, 29.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10144/15290 [05:16<03:01, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10148/15290 [05:16<02:55, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10151/15290 [05:16<02:59, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10154/15290 [05:16<02:58, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10157/15290 [05:16<02:58, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10160/15290 [05:17<03:01, 28.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10164/15290 [05:17<02:59, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
66%|██████▋ | 10167/15290 [05:17<02:58, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10170/15290 [05:17<02:56, 28.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10173/15290 [05:17<02:56, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10176/15290 [05:17<02:55, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10179/15290 [05:17<02:58, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10182/15290 [05:17<02:57, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10186/15290 [05:17<02:55, 29.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10190/15290 [05:18<02:53, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10194/15290 [05:18<02:52, 29.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10198/15290 [05:18<02:51, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10202/15290 [05:18<02:50, 29.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10206/15290 [05:18<02:46, 30.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10210/15290 [05:18<02:50, 29.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10213/15290 [05:18<02:53, 29.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10216/15290 [05:18<02:53, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10219/15290 [05:19<02:53, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10222/15290 [05:19<02:56, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10225/15290 [05:19<02:56, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10228/15290 [05:19<02:55, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10232/15290 [05:19<02:51, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10235/15290 [05:19<02:54, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10238/15290 [05:19<02:59, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10241/15290 [05:19<02:57, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10244/15290 [05:19<02:55, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10247/15290 [05:20<02:56, 28.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10250/15290 [05:20<02:56, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10253/15290 [05:20<02:55, 28.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10256/15290 [05:20<02:56, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10259/15290 [05:20<02:53, 28.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10262/15290 [05:20<02:51, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10265/15290 [05:20<02:55, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10268/15290 [05:20<02:55, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10271/15290 [05:20<02:56, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10274/15290 [05:21<02:54, 28.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10278/15290 [05:21<02:51, 29.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10281/15290 [05:21<02:53, 28.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10284/15290 [05:21<02:56, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10288/15290 [05:21<02:51, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10292/15290 [05:21<02:50, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10295/15290 [05:21<02:56, 28.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10299/15290 [05:21<02:53, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10302/15290 [05:21<02:54, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10305/15290 [05:22<02:54, 28.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10308/15290 [05:22<02:53, 28.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10311/15290 [05:22<03:01, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10314/15290 [05:22<03:01, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10317/15290 [05:22<02:58, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
67%|██████▋ | 10320/15290 [05:22<02:56, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10323/15290 [05:22<02:59, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10326/15290 [05:22<03:00, 27.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10329/15290 [05:22<03:04, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10333/15290 [05:23<02:55, 28.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10337/15290 [05:23<02:49, 29.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10340/15290 [05:23<02:50, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10343/15290 [05:23<02:52, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10346/15290 [05:23<03:01, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10349/15290 [05:23<03:14, 25.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10352/15290 [05:23<03:21, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10355/15290 [05:23<03:25, 24.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10358/15290 [05:24<03:20, 24.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10361/15290 [05:24<03:17, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10364/15290 [05:24<03:12, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10367/15290 [05:24<03:08, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10370/15290 [05:24<03:06, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10373/15290 [05:24<03:10, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10376/15290 [05:24<03:11, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10379/15290 [05:24<03:10, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10382/15290 [05:24<03:05, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10385/15290 [05:25<02:59, 27.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10388/15290 [05:25<03:02, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10391/15290 [05:25<03:00, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10394/15290 [05:25<02:59, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10397/15290 [05:25<02:57, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10400/15290 [05:25<02:56, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10403/15290 [05:25<03:00, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10406/15290 [05:25<03:01, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10409/15290 [05:25<03:00, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10412/15290 [05:26<02:55, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10415/15290 [05:26<02:53, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10418/15290 [05:26<02:53, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10421/15290 [05:26<02:49, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10424/15290 [05:26<02:49, 28.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10427/15290 [05:26<02:48, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10431/15290 [05:26<02:43, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10434/15290 [05:26<02:48, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10437/15290 [05:26<02:51, 28.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10440/15290 [05:27<02:55, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10443/15290 [05:27<03:01, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10447/15290 [05:27<02:57, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10450/15290 [05:27<02:57, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10454/15290 [05:27<02:50, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10457/15290 [05:27<02:49, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10461/15290 [05:27<02:46, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10464/15290 [05:27<02:50, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10467/15290 [05:28<02:48, 28.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10470/15290 [05:28<02:48, 28.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
68%|██████▊ | 10473/15290 [05:28<02:50, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10476/15290 [05:28<02:48, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10479/15290 [05:28<02:50, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10483/15290 [05:28<02:46, 28.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10486/15290 [05:28<02:46, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10489/15290 [05:28<02:44, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10492/15290 [05:28<02:49, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10495/15290 [05:28<02:49, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10498/15290 [05:29<02:49, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10501/15290 [05:29<02:47, 28.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10504/15290 [05:29<02:49, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10508/15290 [05:29<02:43, 29.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▊ | 10511/15290 [05:29<02:42, 29.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10514/15290 [05:29<02:42, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10517/15290 [05:29<02:52, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10520/15290 [05:29<02:51, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10523/15290 [05:29<02:48, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10526/15290 [05:30<02:48, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10530/15290 [05:30<02:40, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10534/15290 [05:30<02:40, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10537/15290 [05:30<02:47, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10540/15290 [05:30<02:46, 28.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10544/15290 [05:30<02:41, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10547/15290 [05:30<02:41, 29.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10550/15290 [05:30<02:46, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10553/15290 [05:31<02:45, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10556/15290 [05:31<02:43, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10560/15290 [05:31<02:39, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10564/15290 [05:31<02:40, 29.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10567/15290 [05:31<02:40, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10571/15290 [05:31<02:38, 29.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10574/15290 [05:31<02:38, 29.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10577/15290 [05:31<02:39, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10580/15290 [05:31<02:41, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10583/15290 [05:32<02:46, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10587/15290 [05:32<02:43, 28.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10591/15290 [05:32<02:39, 29.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10594/15290 [05:32<02:38, 29.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10597/15290 [05:32<02:39, 29.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10600/15290 [05:32<02:40, 29.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10603/15290 [05:32<02:42, 28.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10606/15290 [05:32<02:45, 28.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10609/15290 [05:32<02:45, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10612/15290 [05:33<02:44, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10615/15290 [05:33<02:47, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10618/15290 [05:33<02:48, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10621/15290 [05:33<02:49, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
69%|██████▉ | 10624/15290 [05:33<02:49, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10627/15290 [05:33<02:48, 27.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10630/15290 [05:33<02:48, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10633/15290 [05:33<02:51, 27.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10636/15290 [05:33<02:49, 27.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10639/15290 [05:34<02:45, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10642/15290 [05:34<02:43, 28.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10645/15290 [05:34<02:46, 27.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10648/15290 [05:34<02:45, 28.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10651/15290 [05:34<02:42, 28.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10654/15290 [05:34<02:42, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10657/15290 [05:34<02:58, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10660/15290 [05:34<03:18, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10663/15290 [05:34<03:08, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10666/15290 [05:35<02:59, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10669/15290 [05:35<02:54, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10673/15290 [05:35<02:45, 27.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10677/15290 [05:35<02:41, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10681/15290 [05:35<02:38, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10685/15290 [05:35<02:40, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10688/15290 [05:35<02:46, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10691/15290 [05:35<02:48, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10694/15290 [05:36<02:50, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10697/15290 [05:36<02:48, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|██████▉ | 10700/15290 [05:36<02:49, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10703/15290 [05:36<02:52, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10706/15290 [05:36<02:56, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10709/15290 [05:36<02:49, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10712/15290 [05:36<02:48, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10716/15290 [05:36<02:40, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10719/15290 [05:36<02:42, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10722/15290 [05:37<02:42, 28.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10725/15290 [05:37<02:41, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10729/15290 [05:37<02:38, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10733/15290 [05:37<02:35, 29.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10736/15290 [05:37<02:36, 29.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10740/15290 [05:37<02:33, 29.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10743/15290 [05:37<02:33, 29.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10746/15290 [05:37<03:05, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10749/15290 [05:38<03:09, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10752/15290 [05:38<03:01, 24.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10755/15290 [05:38<02:55, 25.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10759/15290 [05:38<02:42, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10763/15290 [05:38<02:34, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10766/15290 [05:38<02:34, 29.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10769/15290 [05:38<02:35, 29.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10772/15290 [05:38<02:35, 29.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10775/15290 [05:38<02:36, 28.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
70%|███████ | 10778/15290 [05:39<02:36, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10781/15290 [05:39<02:36, 28.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10784/15290 [05:39<02:35, 29.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10787/15290 [05:39<02:35, 28.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10790/15290 [05:39<02:42, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10793/15290 [05:39<02:39, 28.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10797/15290 [05:39<02:33, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10800/15290 [05:39<02:47, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10803/15290 [05:39<02:47, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10806/15290 [05:40<02:49, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10809/15290 [05:40<02:47, 26.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10812/15290 [05:40<02:45, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10816/15290 [05:40<02:37, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10819/15290 [05:40<02:40, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10822/15290 [05:40<02:39, 27.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10825/15290 [05:40<02:41, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10828/15290 [05:40<02:42, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10831/15290 [05:40<02:44, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10834/15290 [05:41<02:43, 27.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10837/15290 [05:41<02:41, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10840/15290 [05:41<02:47, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10843/15290 [05:41<02:46, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10846/15290 [05:41<02:45, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10849/15290 [05:41<02:40, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10852/15290 [05:41<02:41, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10855/15290 [05:41<02:41, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10858/15290 [05:41<02:38, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10861/15290 [05:42<02:41, 27.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10864/15290 [05:42<02:37, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10867/15290 [05:42<02:42, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10870/15290 [05:42<02:40, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10874/15290 [05:42<02:36, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10877/15290 [05:42<02:36, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10881/15290 [05:42<02:31, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10884/15290 [05:42<02:30, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10888/15290 [05:43<02:26, 29.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████ | 10892/15290 [05:43<02:23, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10896/15290 [05:43<02:26, 30.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10900/15290 [05:43<02:28, 29.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10903/15290 [05:43<02:29, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10907/15290 [05:43<02:26, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10911/15290 [05:43<02:24, 30.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10915/15290 [05:43<02:27, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10918/15290 [05:44<02:30, 28.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10921/15290 [05:44<02:33, 28.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10924/15290 [05:44<02:32, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10927/15290 [05:44<02:34, 28.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
71%|███████▏ | 10931/15290 [05:44<02:30, 28.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10934/15290 [05:44<02:30, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10937/15290 [05:44<02:29, 29.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10941/15290 [05:44<02:28, 29.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10944/15290 [05:44<02:30, 28.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10947/15290 [05:45<02:33, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10951/15290 [05:45<02:27, 29.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10954/15290 [05:45<02:29, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10957/15290 [05:45<02:33, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10960/15290 [05:45<02:32, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10964/15290 [05:45<02:26, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10967/15290 [05:45<02:30, 28.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10970/15290 [05:45<02:29, 28.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10974/15290 [05:45<02:25, 29.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10977/15290 [05:46<02:27, 29.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10980/15290 [05:46<02:27, 29.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10984/15290 [05:46<02:20, 30.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10988/15290 [05:46<02:22, 30.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10992/15290 [05:46<02:25, 29.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 10996/15290 [05:46<02:23, 30.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11000/15290 [05:46<02:23, 29.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11003/15290 [05:46<02:24, 29.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11006/15290 [05:47<02:25, 29.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11009/15290 [05:47<02:34, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11013/15290 [05:47<02:30, 28.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11017/15290 [05:47<02:26, 29.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11020/15290 [05:47<02:26, 29.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11024/15290 [05:47<02:23, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11027/15290 [05:47<02:24, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11030/15290 [05:47<02:32, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11033/15290 [05:47<02:33, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11036/15290 [05:48<02:33, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11039/15290 [05:48<02:32, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11043/15290 [05:48<02:27, 28.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11046/15290 [05:48<02:29, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11049/15290 [05:48<02:30, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11052/15290 [05:48<02:32, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11055/15290 [05:48<02:40, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11058/15290 [05:48<02:36, 27.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11061/15290 [05:49<02:37, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11064/15290 [05:49<02:38, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11067/15290 [05:49<02:34, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11071/15290 [05:49<02:26, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11074/15290 [05:49<02:30, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11077/15290 [05:49<02:28, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11080/15290 [05:49<02:33, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
72%|███████▏ | 11083/15290 [05:49<02:36, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11086/15290 [05:49<02:33, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11089/15290 [05:50<02:35, 27.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11092/15290 [05:50<02:39, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11095/15290 [05:50<02:36, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11099/15290 [05:50<02:29, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11102/15290 [05:50<02:28, 28.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11105/15290 [05:50<02:28, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11108/15290 [05:50<02:27, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11111/15290 [05:50<02:30, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11114/15290 [05:50<02:33, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11117/15290 [05:51<02:33, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11120/15290 [05:51<02:31, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11123/15290 [05:51<02:30, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11126/15290 [05:51<02:28, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11129/15290 [05:51<02:26, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11132/15290 [05:51<02:30, 27.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11135/15290 [05:51<02:30, 27.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11139/15290 [05:51<02:26, 28.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11142/15290 [05:51<02:28, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11145/15290 [05:52<02:30, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11148/15290 [05:52<02:31, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11151/15290 [05:52<02:28, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11154/15290 [05:52<02:27, 28.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11157/15290 [05:52<02:26, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11160/15290 [05:52<02:27, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11163/15290 [05:52<02:29, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11166/15290 [05:52<02:30, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11169/15290 [05:52<02:29, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11172/15290 [05:53<02:31, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11175/15290 [05:53<02:28, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11179/15290 [05:53<02:24, 28.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11183/15290 [05:53<02:18, 29.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11186/15290 [05:53<02:18, 29.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11189/15290 [05:53<02:19, 29.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11192/15290 [05:53<02:19, 29.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11195/15290 [05:53<02:24, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11198/15290 [05:53<02:24, 28.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11202/15290 [05:54<02:18, 29.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11206/15290 [05:54<02:16, 29.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11210/15290 [05:54<02:14, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11214/15290 [05:54<02:13, 30.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11218/15290 [05:54<02:14, 30.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11222/15290 [05:54<02:16, 29.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11225/15290 [05:54<02:22, 28.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11228/15290 [05:54<02:22, 28.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11231/15290 [05:55<02:25, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11234/15290 [05:55<02:26, 27.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
73%|███████▎ | 11237/15290 [05:55<02:24, 27.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11240/15290 [05:55<02:27, 27.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11244/15290 [05:55<02:21, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11247/15290 [05:55<02:21, 28.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11250/15290 [05:55<02:21, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11253/15290 [05:55<02:34, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11256/15290 [05:55<02:41, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11259/15290 [05:56<02:46, 24.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11262/15290 [05:56<03:02, 22.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11265/15290 [05:56<03:13, 20.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11268/15290 [05:56<02:58, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11272/15290 [05:56<02:38, 25.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▎ | 11275/15290 [05:56<02:35, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11278/15290 [05:56<02:30, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11281/15290 [05:57<02:31, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11284/15290 [05:57<02:28, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11287/15290 [05:57<02:26, 27.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11290/15290 [05:57<02:29, 26.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11293/15290 [05:57<02:34, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11296/15290 [05:57<02:37, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11299/15290 [05:57<02:50, 23.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11302/15290 [05:57<02:40, 24.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11305/15290 [05:57<02:34, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11308/15290 [05:58<02:52, 23.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11311/15290 [05:58<03:58, 16.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11313/15290 [05:58<04:23, 15.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11315/15290 [05:58<04:23, 15.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11319/15290 [05:58<03:28, 19.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11323/15290 [05:58<02:55, 22.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11326/15290 [05:59<02:49, 23.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11329/15290 [05:59<02:46, 23.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11332/15290 [05:59<02:46, 23.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11335/15290 [05:59<02:44, 24.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11338/15290 [05:59<02:41, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11341/15290 [05:59<02:39, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11344/15290 [05:59<02:42, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11347/15290 [05:59<02:42, 24.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11350/15290 [06:00<02:36, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11353/15290 [06:00<02:35, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11356/15290 [06:00<02:28, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11359/15290 [06:00<02:27, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11362/15290 [06:00<02:22, 27.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11366/15290 [06:00<02:16, 28.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11370/15290 [06:00<02:11, 29.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11373/15290 [06:00<02:12, 29.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11376/15290 [06:00<02:15, 28.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11379/15290 [06:01<02:16, 28.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11382/15290 [06:01<02:19, 28.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11385/15290 [06:01<02:17, 28.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
74%|███████▍ | 11389/15290 [06:01<02:12, 29.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11392/15290 [06:01<02:13, 29.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11395/15290 [06:01<02:15, 28.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11398/15290 [06:01<02:24, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11401/15290 [06:01<02:24, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11405/15290 [06:01<02:18, 28.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11408/15290 [06:02<02:26, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11411/15290 [06:02<02:44, 23.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11414/15290 [06:02<02:44, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11417/15290 [06:02<02:44, 23.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11420/15290 [06:02<02:37, 24.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11424/15290 [06:02<02:26, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11427/15290 [06:02<02:23, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11430/15290 [06:02<02:19, 27.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11434/15290 [06:03<02:15, 28.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11437/15290 [06:03<02:19, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11440/15290 [06:03<02:18, 27.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11443/15290 [06:03<02:17, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11446/15290 [06:03<02:16, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11449/15290 [06:03<02:15, 28.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11452/15290 [06:03<02:16, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11455/15290 [06:03<02:17, 27.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11458/15290 [06:03<02:21, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11461/15290 [06:04<02:20, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11464/15290 [06:04<02:20, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▍ | 11467/15290 [06:04<02:16, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11470/15290 [06:04<02:16, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11473/15290 [06:04<02:17, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11476/15290 [06:04<02:18, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11479/15290 [06:04<02:16, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11482/15290 [06:04<02:19, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11485/15290 [06:04<02:20, 27.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11488/15290 [06:05<02:17, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11491/15290 [06:05<02:16, 27.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11494/15290 [06:05<02:19, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11497/15290 [06:05<02:16, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11500/15290 [06:05<02:16, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11503/15290 [06:05<02:17, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11507/15290 [06:05<02:11, 28.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11510/15290 [06:05<02:12, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11513/15290 [06:05<02:13, 28.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11516/15290 [06:06<02:14, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11519/15290 [06:06<02:17, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11522/15290 [06:06<02:15, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11526/15290 [06:06<02:10, 28.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11530/15290 [06:06<02:06, 29.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11533/15290 [06:06<02:24, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11536/15290 [06:06<02:23, 26.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11539/15290 [06:06<02:19, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
75%|███████▌ | 11543/15290 [06:07<02:12, 28.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11547/15290 [06:07<02:08, 29.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11550/15290 [06:07<02:09, 28.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11553/15290 [06:07<02:12, 28.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11556/15290 [06:07<02:10, 28.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11559/15290 [06:07<02:15, 27.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11562/15290 [06:07<02:13, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11565/15290 [06:07<02:13, 27.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11568/15290 [06:07<02:16, 27.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11571/15290 [06:08<02:20, 26.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11574/15290 [06:08<02:25, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11577/15290 [06:08<02:23, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11580/15290 [06:08<02:24, 25.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11583/15290 [06:08<02:25, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11586/15290 [06:08<02:27, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11589/15290 [06:08<02:21, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11592/15290 [06:08<02:17, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11595/15290 [06:08<02:16, 27.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11598/15290 [06:09<02:17, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11601/15290 [06:09<02:19, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11604/15290 [06:09<02:19, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11608/15290 [06:09<02:11, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11611/15290 [06:09<02:08, 28.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11614/15290 [06:09<02:11, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11617/15290 [06:09<02:10, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11620/15290 [06:09<02:10, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11623/15290 [06:09<02:08, 28.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11626/15290 [06:10<02:08, 28.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11629/15290 [06:10<02:08, 28.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11632/15290 [06:10<02:10, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11635/15290 [06:10<02:13, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11638/15290 [06:10<02:11, 27.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11641/15290 [06:10<02:16, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11644/15290 [06:10<02:18, 26.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11647/15290 [06:10<02:19, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11650/15290 [06:10<02:16, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11653/15290 [06:11<02:14, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▌ | 11656/15290 [06:11<02:14, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11659/15290 [06:11<02:15, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11662/15290 [06:11<02:14, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11665/15290 [06:11<02:10, 27.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11668/15290 [06:11<02:14, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11671/15290 [06:11<02:14, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11674/15290 [06:11<02:15, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11677/15290 [06:11<02:11, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11680/15290 [06:12<02:10, 27.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11683/15290 [06:12<02:11, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11686/15290 [06:12<02:20, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11689/15290 [06:12<02:19, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11692/15290 [06:12<02:16, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
76%|███████▋ | 11695/15290 [06:12<02:12, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11698/15290 [06:12<02:09, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11701/15290 [06:12<02:10, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11704/15290 [06:12<02:14, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11707/15290 [06:13<02:14, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11710/15290 [06:13<02:19, 25.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11713/15290 [06:13<02:14, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11716/15290 [06:13<02:18, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11719/15290 [06:13<02:18, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11722/15290 [06:13<02:16, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11725/15290 [06:13<02:14, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11728/15290 [06:13<02:13, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11731/15290 [06:14<02:13, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11734/15290 [06:14<02:13, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11737/15290 [06:14<02:15, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11740/15290 [06:14<02:20, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11743/15290 [06:14<02:18, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11746/15290 [06:14<02:12, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11749/15290 [06:14<02:15, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11752/15290 [06:14<02:16, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11755/15290 [06:14<02:12, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11758/15290 [06:15<02:12, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11761/15290 [06:15<02:12, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11764/15290 [06:15<02:09, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11767/15290 [06:15<02:07, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11770/15290 [06:15<02:07, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11773/15290 [06:15<02:13, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11776/15290 [06:15<02:15, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11779/15290 [06:15<02:14, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11783/15290 [06:15<02:06, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11786/15290 [06:16<02:05, 27.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11789/15290 [06:16<02:04, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11792/15290 [06:16<02:07, 27.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11795/15290 [06:16<02:06, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11798/15290 [06:16<02:08, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11801/15290 [06:16<02:11, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11804/15290 [06:16<02:09, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11808/15290 [06:16<02:03, 28.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11811/15290 [06:16<02:03, 28.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11814/15290 [06:17<02:02, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11817/15290 [06:17<02:04, 28.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11820/15290 [06:17<02:03, 28.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11823/15290 [06:17<02:07, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11826/15290 [06:17<02:08, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11829/15290 [06:17<02:05, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11832/15290 [06:17<02:06, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11835/15290 [06:17<02:10, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11839/15290 [06:17<02:02, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11843/15290 [06:18<01:59, 28.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11846/15290 [06:18<02:01, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
77%|███████▋ | 11849/15290 [06:18<02:04, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11852/15290 [06:18<02:05, 27.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11855/15290 [06:18<02:07, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11858/15290 [06:18<02:04, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11861/15290 [06:18<02:05, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11864/15290 [06:18<02:09, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11867/15290 [06:19<02:05, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11870/15290 [06:19<02:03, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11873/15290 [06:19<02:05, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11876/15290 [06:19<02:03, 27.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11879/15290 [06:19<02:08, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11882/15290 [06:19<02:06, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11885/15290 [06:19<02:05, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11888/15290 [06:19<02:06, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11891/15290 [06:19<02:09, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11894/15290 [06:20<02:08, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11897/15290 [06:20<02:08, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11900/15290 [06:20<02:05, 27.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11903/15290 [06:20<02:31, 22.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11906/15290 [06:20<02:23, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11909/15290 [06:20<02:16, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11912/15290 [06:20<02:14, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11915/15290 [06:20<02:10, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11918/15290 [06:20<02:05, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11921/15290 [06:21<02:05, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11924/15290 [06:21<02:04, 27.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11927/15290 [06:21<02:04, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11931/15290 [06:21<01:59, 28.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11934/15290 [06:21<02:02, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11937/15290 [06:21<01:59, 28.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11940/15290 [06:21<01:57, 28.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11943/15290 [06:21<02:00, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11947/15290 [06:21<01:56, 28.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11950/15290 [06:22<01:55, 28.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11953/15290 [06:22<01:59, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11956/15290 [06:22<02:00, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11959/15290 [06:22<02:03, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11962/15290 [06:22<02:04, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11965/15290 [06:22<02:04, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11968/15290 [06:22<02:03, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11971/15290 [06:22<02:06, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11974/15290 [06:23<02:09, 25.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11977/15290 [06:23<02:10, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11980/15290 [06:23<02:06, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11983/15290 [06:23<02:01, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11986/15290 [06:23<02:01, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11989/15290 [06:23<02:03, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11992/15290 [06:23<02:00, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11995/15290 [06:23<01:57, 28.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 11998/15290 [06:23<02:03, 26.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
78%|███████▊ | 12001/15290 [06:24<02:05, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12004/15290 [06:24<02:01, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12007/15290 [06:24<01:59, 27.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12010/15290 [06:24<01:57, 27.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12014/15290 [06:24<01:52, 29.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12017/15290 [06:24<01:55, 28.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12020/15290 [06:24<01:55, 28.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12023/15290 [06:24<01:53, 28.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12026/15290 [06:24<01:54, 28.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12029/15290 [06:25<01:57, 27.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12032/15290 [06:25<02:00, 27.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12035/15290 [06:25<01:57, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▊ | 12038/15290 [06:25<01:58, 27.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12041/15290 [06:25<01:58, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12044/15290 [06:25<01:57, 27.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12047/15290 [06:25<01:57, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12050/15290 [06:25<01:57, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12053/15290 [06:25<01:57, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12056/15290 [06:25<01:57, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12059/15290 [06:26<01:58, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12062/15290 [06:26<02:03, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12065/15290 [06:26<02:06, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12068/15290 [06:26<02:05, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12071/15290 [06:26<02:02, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12074/15290 [06:26<02:02, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12077/15290 [06:26<01:59, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12080/15290 [06:26<02:01, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12083/15290 [06:27<02:02, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12086/15290 [06:27<01:59, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12089/15290 [06:27<01:59, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12092/15290 [06:27<02:01, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12095/15290 [06:27<02:00, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12099/15290 [06:27<01:55, 27.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12102/15290 [06:27<01:52, 28.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12105/15290 [06:27<01:56, 27.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12108/15290 [06:27<01:56, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12111/15290 [06:28<01:53, 28.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12114/15290 [06:28<01:52, 28.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12117/15290 [06:28<01:52, 28.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12120/15290 [06:28<01:54, 27.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12123/15290 [06:28<01:55, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12126/15290 [06:28<01:54, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12129/15290 [06:28<01:59, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12132/15290 [06:28<02:13, 23.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12135/15290 [06:28<02:12, 23.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12138/15290 [06:29<02:08, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12141/15290 [06:29<02:04, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12144/15290 [06:29<02:06, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12147/15290 [06:29<02:00, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12150/15290 [06:29<02:04, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
79%|███████▉ | 12153/15290 [06:29<01:58, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12156/15290 [06:29<02:01, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12159/15290 [06:29<02:05, 24.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12162/15290 [06:30<02:02, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12165/15290 [06:30<02:01, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12168/15290 [06:30<02:05, 24.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12171/15290 [06:30<02:13, 23.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12174/15290 [06:30<02:12, 23.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12177/15290 [06:30<02:09, 23.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12180/15290 [06:30<02:07, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12183/15290 [06:30<02:06, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12186/15290 [06:31<02:04, 25.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12189/15290 [06:31<01:59, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12192/15290 [06:31<01:55, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12195/15290 [06:31<01:55, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12198/15290 [06:31<01:51, 27.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12201/15290 [06:31<01:54, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12204/15290 [06:31<01:55, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12207/15290 [06:31<01:55, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12210/15290 [06:31<01:55, 26.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12213/15290 [06:32<01:57, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12216/15290 [06:32<01:58, 25.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12219/15290 [06:32<01:55, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12222/15290 [06:32<01:54, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12225/15290 [06:32<01:56, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12228/15290 [06:32<01:56, 26.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|███████▉ | 12231/15290 [06:32<01:59, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12234/15290 [06:32<01:57, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12237/15290 [06:32<01:55, 26.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12240/15290 [06:33<01:55, 26.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12243/15290 [06:33<01:58, 25.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12246/15290 [06:33<01:54, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12249/15290 [06:33<01:54, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12252/15290 [06:33<01:52, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12255/15290 [06:33<01:55, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12258/15290 [06:33<01:53, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12261/15290 [06:33<02:01, 25.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12264/15290 [06:33<02:01, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12267/15290 [06:34<01:55, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12270/15290 [06:34<01:52, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12273/15290 [06:34<01:49, 27.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12276/15290 [06:34<01:48, 27.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12279/15290 [06:34<01:48, 27.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12282/15290 [06:34<01:50, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12285/15290 [06:34<01:51, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12288/15290 [06:34<01:49, 27.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12291/15290 [06:34<01:53, 26.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12294/15290 [06:35<01:54, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12297/15290 [06:35<01:54, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12300/15290 [06:35<01:50, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12303/15290 [06:35<01:51, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
80%|████████ | 12306/15290 [06:35<01:51, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12309/15290 [06:35<01:52, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12312/15290 [06:35<01:51, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12315/15290 [06:35<01:50, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12318/15290 [06:35<01:49, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12321/15290 [06:36<01:47, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12324/15290 [06:36<01:48, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12327/15290 [06:36<01:48, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12330/15290 [06:36<01:52, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12333/15290 [06:36<01:52, 26.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12336/15290 [06:36<01:50, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12339/15290 [06:36<01:55, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12342/15290 [06:36<01:55, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12345/15290 [06:36<01:52, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12348/15290 [06:37<01:52, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12351/15290 [06:37<01:51, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12354/15290 [06:37<01:55, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12357/15290 [06:37<01:55, 25.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12360/15290 [06:37<01:54, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12363/15290 [06:37<01:52, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12366/15290 [06:37<01:52, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12369/15290 [06:37<01:51, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12372/15290 [06:38<01:51, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12375/15290 [06:38<01:51, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12378/15290 [06:38<01:53, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12381/15290 [06:38<01:49, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12384/15290 [06:38<01:50, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12387/15290 [06:38<01:47, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12390/15290 [06:38<01:50, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12393/15290 [06:38<01:51, 26.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12396/15290 [06:38<01:52, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12399/15290 [06:39<01:49, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12402/15290 [06:39<01:51, 25.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12405/15290 [06:39<01:53, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12408/15290 [06:39<01:53, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12411/15290 [06:39<01:51, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12414/15290 [06:39<01:51, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12417/15290 [06:39<01:47, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12420/15290 [06:39<01:49, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████ | 12423/15290 [06:40<01:53, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12426/15290 [06:40<02:00, 23.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12429/15290 [06:40<01:56, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12432/15290 [06:40<01:53, 25.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12435/15290 [06:40<02:08, 22.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12438/15290 [06:40<02:04, 22.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12441/15290 [06:40<02:02, 23.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12444/15290 [06:40<01:57, 24.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12447/15290 [06:41<01:56, 24.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12450/15290 [06:41<01:53, 25.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12453/15290 [06:41<01:50, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12456/15290 [06:41<01:47, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
81%|████████▏ | 12459/15290 [06:41<01:44, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12462/15290 [06:41<01:44, 27.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12465/15290 [06:41<01:43, 27.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12468/15290 [06:41<01:43, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12471/15290 [06:41<01:43, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12474/15290 [06:42<01:43, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12477/15290 [06:42<01:41, 27.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12480/15290 [06:42<01:42, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12483/15290 [06:42<01:42, 27.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12486/15290 [06:42<01:42, 27.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12489/15290 [06:42<01:45, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12492/15290 [06:42<01:44, 26.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12495/15290 [06:42<01:42, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12498/15290 [06:42<01:45, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12501/15290 [06:43<01:44, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12504/15290 [06:43<01:43, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12507/15290 [06:43<01:41, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12510/15290 [06:43<01:40, 27.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12513/15290 [06:43<01:41, 27.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12516/15290 [06:43<01:42, 26.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12519/15290 [06:43<01:45, 26.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12522/15290 [06:43<01:54, 24.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12525/15290 [06:43<02:02, 22.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12528/15290 [06:44<01:58, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12531/15290 [06:44<01:55, 23.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12534/15290 [06:44<01:52, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12537/15290 [06:44<01:49, 25.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12540/15290 [06:44<01:56, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12543/15290 [06:44<01:49, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12546/15290 [06:44<01:48, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12549/15290 [06:44<01:48, 25.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12552/15290 [06:45<01:48, 25.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12555/15290 [06:45<01:46, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12558/15290 [06:45<01:45, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12561/15290 [06:45<01:44, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12564/15290 [06:45<01:44, 26.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12567/15290 [06:45<01:43, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12570/15290 [06:45<01:44, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12573/15290 [06:45<01:42, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12576/15290 [06:45<01:43, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12579/15290 [06:46<01:43, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12582/15290 [06:46<01:44, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12585/15290 [06:46<01:42, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12588/15290 [06:46<01:41, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12591/15290 [06:46<01:45, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12594/15290 [06:46<01:49, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12597/15290 [06:46<01:45, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12600/15290 [06:46<01:48, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12603/15290 [06:47<01:45, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12606/15290 [06:47<01:45, 25.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12609/15290 [06:47<01:44, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
82%|████████▏ | 12612/15290 [06:47<01:43, 25.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12615/15290 [06:47<01:42, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12618/15290 [06:47<01:40, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12621/15290 [06:47<01:39, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12624/15290 [06:47<01:39, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12627/15290 [06:47<01:40, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12630/15290 [06:48<01:41, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12633/15290 [06:48<01:39, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12636/15290 [06:48<01:41, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12639/15290 [06:48<01:42, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12642/15290 [06:48<01:43, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12645/15290 [06:48<01:44, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12648/15290 [06:48<01:42, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12651/15290 [06:48<01:43, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12654/15290 [06:48<01:44, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12657/15290 [06:49<01:44, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12660/15290 [06:49<01:42, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12663/15290 [06:49<01:40, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12666/15290 [06:49<01:43, 25.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12669/15290 [06:49<01:44, 25.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12672/15290 [06:49<01:44, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12675/15290 [06:49<01:45, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12678/15290 [06:49<01:45, 24.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12681/15290 [06:50<01:41, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12684/15290 [06:50<01:38, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12687/15290 [06:50<01:37, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12690/15290 [06:50<01:34, 27.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12693/15290 [06:50<01:36, 27.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12696/15290 [06:50<01:36, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12699/15290 [06:50<01:38, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12702/15290 [06:50<01:39, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12705/15290 [06:50<01:37, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12708/15290 [06:51<01:36, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12711/15290 [06:51<01:36, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12714/15290 [06:51<01:35, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12717/15290 [06:51<01:34, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12720/15290 [06:51<01:32, 27.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12723/15290 [06:51<01:32, 27.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12726/15290 [06:51<01:31, 28.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12729/15290 [06:51<01:31, 27.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12732/15290 [06:51<01:33, 27.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12735/15290 [06:52<01:33, 27.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12738/15290 [06:52<01:34, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12741/15290 [06:52<01:35, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12744/15290 [06:52<01:36, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12747/15290 [06:52<01:35, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12750/15290 [06:52<01:36, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12753/15290 [06:52<01:35, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12756/15290 [06:52<01:36, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12759/15290 [06:52<01:35, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12762/15290 [06:53<01:33, 27.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
83%|████████▎ | 12765/15290 [06:53<01:32, 27.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12768/15290 [06:53<01:33, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12771/15290 [06:53<01:33, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12774/15290 [06:53<01:34, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12777/15290 [06:53<01:34, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12780/15290 [06:53<01:33, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12783/15290 [06:53<01:34, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12786/15290 [06:53<01:34, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12789/15290 [06:54<01:33, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12792/15290 [06:54<01:32, 26.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12795/15290 [06:54<01:34, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12798/15290 [06:54<01:36, 25.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12801/15290 [06:54<01:33, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▎ | 12804/15290 [06:54<01:33, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12807/15290 [06:54<01:33, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12810/15290 [06:54<01:33, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12813/15290 [06:54<01:32, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12816/15290 [06:55<01:32, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12819/15290 [06:55<01:32, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12822/15290 [06:55<01:32, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12825/15290 [06:55<01:33, 26.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12828/15290 [06:55<01:31, 26.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12831/15290 [06:55<01:31, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12834/15290 [06:55<01:34, 26.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12837/15290 [06:55<01:35, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12840/15290 [06:55<01:33, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12843/15290 [06:56<01:32, 26.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12846/15290 [06:56<01:32, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12849/15290 [06:56<01:30, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12852/15290 [06:56<01:31, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12855/15290 [06:56<01:33, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12858/15290 [06:56<01:34, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12861/15290 [06:56<01:32, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12864/15290 [06:56<01:31, 26.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12867/15290 [06:56<01:30, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12870/15290 [06:57<01:29, 26.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12873/15290 [06:57<01:29, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12876/15290 [06:57<01:28, 27.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12879/15290 [06:57<01:30, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12882/15290 [06:57<01:31, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12885/15290 [06:57<01:32, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12888/15290 [06:57<01:29, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12891/15290 [06:57<01:28, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12894/15290 [06:58<01:30, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12897/15290 [06:58<01:30, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12900/15290 [06:58<01:31, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12903/15290 [06:58<01:28, 27.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12906/15290 [06:58<01:28, 27.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12909/15290 [06:58<01:29, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12912/15290 [06:58<01:29, 26.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12915/15290 [06:58<01:29, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
84%|████████▍ | 12918/15290 [06:58<01:30, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12921/15290 [06:59<01:30, 26.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12924/15290 [06:59<01:30, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12927/15290 [06:59<01:27, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12930/15290 [06:59<01:29, 26.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12933/15290 [06:59<01:28, 26.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12936/15290 [06:59<01:26, 27.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12939/15290 [06:59<01:26, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12942/15290 [06:59<01:29, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12945/15290 [06:59<01:33, 24.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12948/15290 [07:00<01:29, 26.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12951/15290 [07:00<01:28, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12954/15290 [07:00<01:29, 26.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12957/15290 [07:00<01:28, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12960/15290 [07:00<01:31, 25.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12963/15290 [07:00<01:29, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12966/15290 [07:00<01:27, 26.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12969/15290 [07:00<01:26, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12972/15290 [07:00<01:26, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12975/15290 [07:01<01:24, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12978/15290 [07:01<01:28, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12981/15290 [07:01<01:28, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12984/15290 [07:01<01:30, 25.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12987/15290 [07:01<01:38, 23.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12990/15290 [07:01<01:40, 22.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12993/15290 [07:01<01:38, 23.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▍ | 12996/15290 [07:01<01:35, 24.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 12999/15290 [07:02<01:33, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13002/15290 [07:02<01:33, 24.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13005/15290 [07:02<01:30, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13008/15290 [07:02<01:27, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13011/15290 [07:02<01:25, 26.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13014/15290 [07:02<01:23, 27.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13017/15290 [07:02<01:22, 27.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13020/15290 [07:02<01:22, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13023/15290 [07:02<01:24, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13026/15290 [07:03<01:21, 27.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13029/15290 [07:03<01:23, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13032/15290 [07:03<01:28, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13035/15290 [07:03<01:30, 24.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13038/15290 [07:03<01:34, 23.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13041/15290 [07:03<01:32, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13044/15290 [07:03<01:30, 24.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13047/15290 [07:03<01:29, 24.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13050/15290 [07:04<01:30, 24.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13053/15290 [07:04<01:30, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13056/15290 [07:04<01:27, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13059/15290 [07:04<01:25, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13062/15290 [07:04<01:24, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13065/15290 [07:04<01:26, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13068/15290 [07:04<01:28, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
85%|████████▌ | 13071/15290 [07:04<01:28, 25.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13074/15290 [07:04<01:25, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13077/15290 [07:05<01:25, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13080/15290 [07:05<01:25, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13083/15290 [07:05<01:24, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13086/15290 [07:05<01:25, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13089/15290 [07:05<01:28, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13092/15290 [07:05<01:30, 24.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13095/15290 [07:05<01:32, 23.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13098/15290 [07:05<01:31, 23.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13101/15290 [07:06<01:30, 24.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13104/15290 [07:06<01:27, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13107/15290 [07:06<01:25, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13110/15290 [07:06<01:21, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13113/15290 [07:06<01:20, 27.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13116/15290 [07:06<01:23, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13119/15290 [07:06<01:22, 26.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13122/15290 [07:06<01:23, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13125/15290 [07:06<01:22, 26.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13128/15290 [07:07<01:23, 25.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13131/15290 [07:07<01:21, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13134/15290 [07:07<01:22, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13137/15290 [07:07<01:21, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13140/15290 [07:07<01:21, 26.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13143/15290 [07:07<01:19, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13146/15290 [07:07<01:18, 27.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13149/15290 [07:07<01:16, 27.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13152/15290 [07:07<01:19, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13155/15290 [07:08<01:19, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13158/15290 [07:08<01:20, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13161/15290 [07:08<01:19, 26.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13164/15290 [07:08<01:20, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13167/15290 [07:08<01:20, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13170/15290 [07:08<01:21, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13173/15290 [07:08<01:21, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13176/15290 [07:08<01:24, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13179/15290 [07:09<01:21, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13182/15290 [07:09<01:22, 25.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▌ | 13185/15290 [07:09<01:20, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13188/15290 [07:09<01:19, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13191/15290 [07:09<01:21, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13194/15290 [07:09<01:18, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13197/15290 [07:09<01:18, 26.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13200/15290 [07:09<01:19, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13203/15290 [07:09<01:19, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13206/15290 [07:10<01:17, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13209/15290 [07:10<01:17, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13212/15290 [07:10<01:18, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13215/15290 [07:10<01:15, 27.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13218/15290 [07:10<01:17, 26.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13221/15290 [07:10<01:20, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
86%|████████▋ | 13224/15290 [07:10<01:24, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13227/15290 [07:10<01:24, 24.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13230/15290 [07:10<01:22, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13233/15290 [07:11<01:21, 25.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13236/15290 [07:11<01:19, 25.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13239/15290 [07:11<01:19, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13242/15290 [07:11<01:18, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13245/15290 [07:11<01:18, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13248/15290 [07:11<01:17, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13251/15290 [07:11<01:17, 26.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13254/15290 [07:11<01:18, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13257/15290 [07:12<01:17, 26.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13260/15290 [07:12<01:15, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13263/15290 [07:12<01:16, 26.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13266/15290 [07:12<01:14, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13269/15290 [07:12<01:13, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13272/15290 [07:12<01:13, 27.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13275/15290 [07:12<01:11, 28.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13278/15290 [07:12<01:13, 27.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13281/15290 [07:12<01:14, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13284/15290 [07:13<01:15, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13287/15290 [07:13<01:16, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13290/15290 [07:13<01:16, 26.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13293/15290 [07:13<01:17, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13296/15290 [07:13<01:16, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13299/15290 [07:13<01:15, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13302/15290 [07:13<01:15, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13305/15290 [07:13<01:14, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13308/15290 [07:13<01:17, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13311/15290 [07:14<01:16, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13314/15290 [07:14<01:14, 26.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13317/15290 [07:14<01:16, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13320/15290 [07:14<01:16, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13323/15290 [07:14<01:13, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13326/15290 [07:14<01:14, 26.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13329/15290 [07:14<01:12, 26.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13332/15290 [07:14<01:13, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13335/15290 [07:14<01:17, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13338/15290 [07:15<01:18, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13341/15290 [07:15<01:16, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13344/15290 [07:15<01:14, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13347/15290 [07:15<01:12, 26.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13350/15290 [07:15<01:12, 26.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13353/15290 [07:15<01:11, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13356/15290 [07:15<01:11, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13359/15290 [07:15<01:16, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13362/15290 [07:15<01:13, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13365/15290 [07:16<01:12, 26.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13368/15290 [07:16<01:11, 26.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13371/15290 [07:16<01:11, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13374/15290 [07:16<01:11, 26.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
87%|████████▋ | 13377/15290 [07:16<01:12, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13380/15290 [07:16<01:13, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13383/15290 [07:16<01:17, 24.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13386/15290 [07:16<01:19, 23.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13389/15290 [07:17<01:15, 25.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13392/15290 [07:17<01:14, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13395/15290 [07:17<01:16, 24.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13398/15290 [07:17<01:15, 24.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13401/15290 [07:17<01:14, 25.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13404/15290 [07:17<01:11, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13407/15290 [07:17<01:10, 26.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13410/15290 [07:17<01:11, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13413/15290 [07:17<01:10, 26.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13416/15290 [07:18<01:12, 25.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13419/15290 [07:18<01:14, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13422/15290 [07:18<01:16, 24.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13425/15290 [07:18<01:16, 24.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13428/15290 [07:18<01:17, 24.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13431/15290 [07:18<01:14, 24.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13434/15290 [07:18<01:12, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13437/15290 [07:18<01:13, 25.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13440/15290 [07:19<01:24, 21.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13443/15290 [07:19<01:31, 20.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13446/15290 [07:19<01:28, 20.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13449/15290 [07:19<01:21, 22.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13452/15290 [07:19<01:17, 23.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13455/15290 [07:19<01:17, 23.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13458/15290 [07:19<01:16, 23.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13461/15290 [07:20<01:15, 24.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13464/15290 [07:20<01:15, 24.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13467/15290 [07:20<01:15, 24.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13470/15290 [07:20<01:16, 23.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13473/15290 [07:20<01:16, 23.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13476/15290 [07:20<01:18, 23.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13479/15290 [07:20<01:17, 23.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13482/15290 [07:20<01:18, 23.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13485/15290 [07:21<01:16, 23.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13488/15290 [07:21<01:17, 23.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13491/15290 [07:21<01:16, 23.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13494/15290 [07:21<01:20, 22.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13497/15290 [07:21<01:21, 22.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13500/15290 [07:21<01:19, 22.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13503/15290 [07:21<01:16, 23.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13506/15290 [07:21<01:15, 23.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13509/15290 [07:22<01:15, 23.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13512/15290 [07:22<01:13, 24.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13515/15290 [07:22<01:10, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13518/15290 [07:22<01:08, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13521/15290 [07:22<01:07, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13524/15290 [07:22<01:06, 26.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13527/15290 [07:22<01:05, 26.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
88%|████████▊ | 13530/15290 [07:22<01:06, 26.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13533/15290 [07:22<01:05, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13536/15290 [07:23<01:06, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13539/15290 [07:23<01:07, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13542/15290 [07:23<01:07, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13545/15290 [07:23<01:06, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13548/15290 [07:23<01:05, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13551/15290 [07:23<01:06, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13554/15290 [07:23<01:04, 26.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13557/15290 [07:23<01:05, 26.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13560/15290 [07:24<01:06, 26.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13563/15290 [07:24<01:05, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13566/15290 [07:24<01:04, 26.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▊ | 13569/15290 [07:24<01:03, 27.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13572/15290 [07:24<01:03, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13575/15290 [07:24<01:03, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13578/15290 [07:24<01:28, 19.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13581/15290 [07:24<01:20, 21.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13584/15290 [07:25<01:17, 22.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13587/15290 [07:25<01:12, 23.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13590/15290 [07:25<01:11, 23.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13593/15290 [07:25<01:09, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13596/15290 [07:25<01:06, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13599/15290 [07:25<01:06, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13602/15290 [07:25<01:05, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13605/15290 [07:25<01:05, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13608/15290 [07:25<01:04, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13611/15290 [07:26<01:03, 26.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13614/15290 [07:26<01:03, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13617/15290 [07:26<01:02, 26.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13620/15290 [07:26<01:02, 26.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13623/15290 [07:26<01:02, 26.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13626/15290 [07:26<01:02, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13629/15290 [07:26<01:02, 26.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13632/15290 [07:26<01:05, 25.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13635/15290 [07:26<01:05, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13638/15290 [07:27<01:07, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13641/15290 [07:27<01:06, 24.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13644/15290 [07:27<01:06, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13647/15290 [07:27<01:06, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13650/15290 [07:27<01:05, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13653/15290 [07:27<01:03, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13656/15290 [07:27<01:03, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13659/15290 [07:27<01:03, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13662/15290 [07:28<01:03, 25.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13665/15290 [07:28<01:03, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13668/15290 [07:28<01:04, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13671/15290 [07:28<01:03, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13674/15290 [07:28<01:02, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13677/15290 [07:28<01:02, 25.85it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13680/15290 [07:28<01:01, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
89%|████████▉ | 13683/15290 [07:28<01:01, 26.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13686/15290 [07:28<01:01, 26.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13689/15290 [07:29<01:02, 25.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13692/15290 [07:29<01:02, 25.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13695/15290 [07:29<01:02, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13698/15290 [07:29<01:02, 25.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13701/15290 [07:29<01:01, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13704/15290 [07:29<01:02, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13707/15290 [07:29<01:01, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13710/15290 [07:29<01:02, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13713/15290 [07:30<01:01, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13716/15290 [07:30<01:01, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13719/15290 [07:30<01:08, 22.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13722/15290 [07:30<01:05, 24.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13725/15290 [07:30<01:04, 24.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13728/15290 [07:30<01:02, 25.12it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13731/15290 [07:30<01:02, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13734/15290 [07:30<01:01, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13737/15290 [07:31<01:01, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13740/15290 [07:31<01:02, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13743/15290 [07:31<01:01, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13746/15290 [07:31<01:01, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13749/15290 [07:31<01:00, 25.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13752/15290 [07:31<00:59, 25.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13755/15290 [07:31<00:59, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|████████▉ | 13758/15290 [07:31<01:02, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13761/15290 [07:31<01:00, 25.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13764/15290 [07:32<00:58, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13767/15290 [07:32<00:57, 26.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13770/15290 [07:32<00:56, 26.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13773/15290 [07:32<00:57, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13776/15290 [07:32<00:58, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13779/15290 [07:32<00:59, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13782/15290 [07:32<00:59, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13785/15290 [07:32<01:00, 24.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13788/15290 [07:33<00:59, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13791/15290 [07:33<01:00, 24.61it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13794/15290 [07:33<01:00, 24.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13797/15290 [07:33<00:59, 24.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13800/15290 [07:33<00:59, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13803/15290 [07:33<00:59, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13806/15290 [07:33<00:58, 25.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13809/15290 [07:33<00:58, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13812/15290 [07:33<00:57, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13815/15290 [07:34<00:57, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13818/15290 [07:34<00:59, 24.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13821/15290 [07:34<00:58, 25.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13824/15290 [07:34<00:59, 24.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13827/15290 [07:34<00:59, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13830/15290 [07:34<01:01, 23.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13833/15290 [07:34<01:02, 23.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
90%|█████████ | 13836/15290 [07:34<01:02, 23.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13839/15290 [07:35<01:02, 23.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13842/15290 [07:35<01:02, 23.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13845/15290 [07:35<01:01, 23.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13848/15290 [07:35<01:01, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13851/15290 [07:35<01:01, 23.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13854/15290 [07:35<01:01, 23.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13857/15290 [07:35<00:58, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13860/15290 [07:35<00:56, 25.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13863/15290 [07:36<00:55, 25.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13866/15290 [07:36<00:56, 25.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13869/15290 [07:36<00:57, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13872/15290 [07:36<00:58, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13875/15290 [07:36<00:59, 23.89it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13878/15290 [07:36<00:58, 24.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13881/15290 [07:36<01:00, 23.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13884/15290 [07:36<01:00, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13887/15290 [07:37<01:01, 22.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13890/15290 [07:37<01:00, 23.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13893/15290 [07:37<01:00, 23.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13896/15290 [07:37<01:00, 22.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13899/15290 [07:37<01:02, 22.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13902/15290 [07:37<01:03, 21.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13905/15290 [07:37<01:03, 21.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13908/15290 [07:38<01:02, 22.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13911/15290 [07:38<01:00, 22.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13914/15290 [07:38<00:59, 23.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13917/15290 [07:38<01:02, 22.00it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13920/15290 [07:38<01:02, 21.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13923/15290 [07:38<01:01, 22.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13926/15290 [07:38<00:59, 22.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13929/15290 [07:38<00:57, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13932/15290 [07:39<00:55, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13935/15290 [07:39<00:54, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13938/15290 [07:39<00:54, 24.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13941/15290 [07:39<00:53, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13944/15290 [07:39<00:52, 25.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13947/15290 [07:39<00:52, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████ | 13950/15290 [07:39<00:54, 24.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13953/15290 [07:39<00:55, 24.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13956/15290 [07:40<00:53, 24.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13959/15290 [07:40<00:54, 24.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13962/15290 [07:40<00:58, 22.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13965/15290 [07:40<00:57, 22.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13968/15290 [07:40<00:58, 22.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13971/15290 [07:40<01:00, 21.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13974/15290 [07:40<01:01, 21.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13977/15290 [07:40<00:58, 22.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13980/15290 [07:41<00:55, 23.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13983/15290 [07:41<00:54, 24.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13986/15290 [07:41<00:53, 24.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
91%|█████████▏| 13989/15290 [07:41<00:53, 24.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 13992/15290 [07:41<00:51, 25.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 13995/15290 [07:41<00:49, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 13998/15290 [07:41<00:48, 26.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14001/15290 [07:41<00:50, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14004/15290 [07:42<00:49, 25.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14007/15290 [07:42<00:49, 25.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14010/15290 [07:42<00:50, 25.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14013/15290 [07:42<00:49, 25.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14016/15290 [07:42<00:50, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14019/15290 [07:42<00:51, 24.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14022/15290 [07:42<00:51, 24.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14025/15290 [07:42<00:51, 24.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14028/15290 [07:43<00:50, 24.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14031/15290 [07:43<00:49, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14034/15290 [07:43<00:50, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14037/15290 [07:43<00:49, 25.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14040/15290 [07:43<00:48, 25.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14043/15290 [07:43<00:49, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14046/15290 [07:43<00:49, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14049/15290 [07:43<00:48, 25.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14052/15290 [07:43<00:49, 25.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14055/15290 [07:44<00:50, 24.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14058/15290 [07:44<00:50, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14061/15290 [07:44<00:50, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14064/15290 [07:44<00:49, 24.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14067/15290 [07:44<00:47, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14070/15290 [07:44<00:46, 26.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14073/15290 [07:44<00:45, 26.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14076/15290 [07:44<00:45, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14079/15290 [07:44<00:45, 26.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14082/15290 [07:45<00:44, 26.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14085/15290 [07:45<00:44, 26.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14088/15290 [07:45<00:44, 26.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14091/15290 [07:45<00:44, 26.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14094/15290 [07:45<00:44, 26.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14097/15290 [07:45<00:43, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14100/15290 [07:45<00:43, 27.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14103/15290 [07:45<00:44, 26.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14106/15290 [07:45<00:43, 27.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14109/15290 [07:46<00:43, 27.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14112/15290 [07:46<00:43, 27.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14115/15290 [07:46<00:42, 27.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14118/15290 [07:46<00:41, 27.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14121/15290 [07:46<00:41, 27.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14124/15290 [07:46<00:42, 27.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14127/15290 [07:46<00:42, 27.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14130/15290 [07:46<00:43, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14133/15290 [07:46<00:43, 26.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14136/15290 [07:47<00:43, 26.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14139/15290 [07:47<00:44, 25.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
92%|█████████▏| 14142/15290 [07:47<00:45, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14145/15290 [07:47<00:45, 25.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14148/15290 [07:47<00:44, 25.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14151/15290 [07:47<00:43, 25.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14154/15290 [07:47<00:46, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14157/15290 [07:47<00:46, 24.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14160/15290 [07:48<00:44, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14163/15290 [07:48<00:44, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14166/15290 [07:48<00:43, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14169/15290 [07:48<00:45, 24.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14172/15290 [07:48<00:47, 23.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14175/15290 [07:48<00:50, 22.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14178/15290 [07:48<00:50, 22.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14181/15290 [07:48<00:48, 22.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14184/15290 [07:49<00:46, 23.56it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14187/15290 [07:49<00:45, 24.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14190/15290 [07:49<00:47, 23.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14193/15290 [07:49<00:46, 23.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14196/15290 [07:49<00:45, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14199/15290 [07:49<00:44, 24.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14202/15290 [07:49<00:44, 24.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14205/15290 [07:49<00:45, 24.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14208/15290 [07:50<00:45, 23.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14211/15290 [07:50<00:43, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14214/15290 [07:50<00:43, 24.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14217/15290 [07:50<00:43, 24.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14220/15290 [07:50<00:43, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14223/15290 [07:50<00:43, 24.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14226/15290 [07:50<00:43, 24.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14229/15290 [07:50<00:44, 23.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14232/15290 [07:51<00:48, 21.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14235/15290 [07:51<00:46, 22.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14238/15290 [07:51<00:48, 21.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14241/15290 [07:51<00:49, 21.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14244/15290 [07:51<00:46, 22.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14247/15290 [07:51<00:46, 22.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14250/15290 [07:51<00:45, 22.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14253/15290 [07:52<00:46, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14256/15290 [07:52<00:46, 22.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14259/15290 [07:52<00:44, 22.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14262/15290 [07:52<00:44, 23.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14265/15290 [07:52<00:43, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14268/15290 [07:52<00:44, 23.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14271/15290 [07:52<00:45, 22.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14274/15290 [07:52<00:43, 23.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14277/15290 [07:53<00:42, 23.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14280/15290 [07:53<00:42, 23.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14283/15290 [07:53<00:41, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14286/15290 [07:53<00:40, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14289/15290 [07:53<00:42, 23.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14292/15290 [07:53<00:43, 23.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
93%|█████████▎| 14295/15290 [07:53<00:42, 23.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14298/15290 [07:53<00:41, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14301/15290 [07:54<00:40, 24.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14304/15290 [07:54<00:40, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14307/15290 [07:54<00:38, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14310/15290 [07:54<00:36, 26.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14313/15290 [07:54<00:36, 26.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14316/15290 [07:54<00:35, 27.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14319/15290 [07:54<00:35, 27.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14322/15290 [07:54<00:35, 27.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14325/15290 [07:54<00:35, 26.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14328/15290 [07:55<00:36, 26.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14331/15290 [07:55<00:36, 26.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▎| 14334/15290 [07:55<00:36, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14337/15290 [07:55<00:37, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14340/15290 [07:55<00:37, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14343/15290 [07:55<00:36, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14346/15290 [07:55<00:36, 26.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14349/15290 [07:55<00:36, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14352/15290 [07:56<00:36, 25.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14355/15290 [07:56<00:36, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14358/15290 [07:56<00:36, 25.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14361/15290 [07:56<00:36, 25.45it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14364/15290 [07:56<00:36, 25.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14367/15290 [07:56<00:35, 26.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14370/15290 [07:56<00:35, 26.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14373/15290 [07:56<00:35, 26.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14376/15290 [07:56<00:35, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14379/15290 [07:57<00:35, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14382/15290 [07:57<00:34, 26.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14385/15290 [07:57<00:34, 25.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14388/15290 [07:57<00:34, 26.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14391/15290 [07:57<00:35, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14394/15290 [07:57<00:35, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14397/15290 [07:57<00:35, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14400/15290 [07:57<00:35, 25.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14403/15290 [07:57<00:34, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14406/15290 [07:58<00:34, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14409/15290 [07:58<00:34, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14412/15290 [07:58<00:33, 26.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14415/15290 [07:58<00:33, 26.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14418/15290 [07:58<00:33, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14421/15290 [07:58<00:33, 26.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14424/15290 [07:58<00:33, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14427/15290 [07:58<00:33, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14430/15290 [07:59<00:33, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14433/15290 [07:59<00:33, 25.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14436/15290 [07:59<00:34, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14439/15290 [07:59<00:33, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14442/15290 [07:59<00:33, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14445/15290 [07:59<00:34, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
94%|█████████▍| 14448/15290 [07:59<00:33, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14451/15290 [07:59<00:33, 25.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14454/15290 [07:59<00:33, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14457/15290 [08:00<00:33, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14460/15290 [08:00<00:32, 25.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14463/15290 [08:00<00:31, 25.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14466/15290 [08:00<00:32, 25.64it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14469/15290 [08:00<00:31, 25.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14472/15290 [08:00<00:31, 25.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14475/15290 [08:00<00:31, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14478/15290 [08:00<00:31, 25.72it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14481/15290 [08:01<00:31, 25.83it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14484/15290 [08:01<00:30, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14487/15290 [08:01<00:31, 25.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14490/15290 [08:01<00:31, 25.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14493/15290 [08:01<00:31, 25.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14496/15290 [08:01<00:31, 25.13it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14499/15290 [08:01<00:31, 24.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14502/15290 [08:01<00:31, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14505/15290 [08:02<00:32, 24.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14508/15290 [08:02<00:31, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14511/15290 [08:02<00:31, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14514/15290 [08:02<00:30, 25.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14517/15290 [08:02<00:29, 25.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14520/15290 [08:02<00:29, 26.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▍| 14523/15290 [08:02<00:29, 26.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14526/15290 [08:02<00:28, 26.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14529/15290 [08:02<00:28, 26.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14532/15290 [08:03<00:28, 26.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14535/15290 [08:03<00:28, 26.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14538/15290 [08:03<00:28, 25.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14541/15290 [08:03<00:29, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14544/15290 [08:03<00:29, 25.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14547/15290 [08:03<00:28, 25.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14550/15290 [08:03<00:29, 25.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14553/15290 [08:03<00:30, 23.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14556/15290 [08:03<00:30, 24.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14559/15290 [08:04<00:29, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14562/15290 [08:04<00:28, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14565/15290 [08:04<00:28, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14568/15290 [08:04<00:28, 24.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14571/15290 [08:04<00:29, 24.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14574/15290 [08:04<00:29, 24.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14577/15290 [08:04<00:29, 23.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14580/15290 [08:04<00:29, 24.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14583/15290 [08:05<00:30, 23.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14586/15290 [08:05<00:30, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14589/15290 [08:05<00:29, 23.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14592/15290 [08:05<00:29, 23.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14595/15290 [08:05<00:28, 24.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14598/15290 [08:05<00:28, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
95%|█████████▌| 14601/15290 [08:05<00:28, 24.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14604/15290 [08:05<00:27, 24.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14607/15290 [08:06<00:28, 24.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14610/15290 [08:06<00:27, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14613/15290 [08:06<00:27, 24.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14616/15290 [08:06<00:26, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14619/15290 [08:06<00:26, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14622/15290 [08:06<00:26, 25.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14625/15290 [08:06<00:26, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14628/15290 [08:06<00:26, 25.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14631/15290 [08:07<00:26, 25.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14634/15290 [08:07<00:26, 25.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14637/15290 [08:07<00:25, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14640/15290 [08:07<00:25, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14643/15290 [08:07<00:25, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14646/15290 [08:07<00:25, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14649/15290 [08:07<00:26, 24.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14652/15290 [08:07<00:25, 24.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14655/15290 [08:08<00:26, 23.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14658/15290 [08:08<00:25, 24.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14661/15290 [08:08<00:25, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14664/15290 [08:08<00:26, 24.04it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14667/15290 [08:08<00:25, 24.03it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14670/15290 [08:08<00:25, 23.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14673/15290 [08:08<00:25, 24.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14676/15290 [08:08<00:25, 24.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14679/15290 [08:08<00:24, 24.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14682/15290 [08:09<00:24, 24.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14685/15290 [08:09<00:24, 24.90it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14688/15290 [08:09<00:24, 24.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14691/15290 [08:09<00:24, 24.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14694/15290 [08:09<00:24, 24.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14697/15290 [08:09<00:23, 24.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14700/15290 [08:09<00:23, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14703/15290 [08:09<00:23, 24.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14706/15290 [08:10<00:24, 23.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14709/15290 [08:10<00:24, 23.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14712/15290 [08:10<00:23, 24.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▌| 14715/15290 [08:10<00:23, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14718/15290 [08:10<00:24, 23.71it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14721/15290 [08:10<00:24, 23.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14724/15290 [08:10<00:23, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14727/15290 [08:10<00:23, 24.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14730/15290 [08:11<00:23, 23.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14733/15290 [08:11<00:23, 24.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14736/15290 [08:11<00:23, 23.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14739/15290 [08:11<00:22, 24.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14742/15290 [08:11<00:21, 24.97it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14745/15290 [08:11<00:21, 25.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14748/15290 [08:11<00:20, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14751/15290 [08:11<00:20, 26.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
96%|█████████▋| 14754/15290 [08:12<00:22, 24.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14757/15290 [08:12<00:22, 23.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14760/15290 [08:12<00:22, 23.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14763/15290 [08:12<00:22, 23.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14766/15290 [08:12<00:22, 23.40it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14769/15290 [08:12<00:22, 23.46it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14772/15290 [08:12<00:24, 21.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14775/15290 [08:12<00:22, 22.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14778/15290 [08:13<00:22, 23.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14781/15290 [08:13<00:21, 24.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14784/15290 [08:13<00:20, 24.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14787/15290 [08:13<00:20, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14790/15290 [08:13<00:20, 24.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14793/15290 [08:13<00:19, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14796/15290 [08:13<00:19, 24.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14799/15290 [08:13<00:19, 24.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14802/15290 [08:14<00:19, 24.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14805/15290 [08:14<00:19, 25.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14808/15290 [08:14<00:19, 25.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14811/15290 [08:14<00:19, 24.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14814/15290 [08:14<00:18, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14817/15290 [08:14<00:18, 25.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14820/15290 [08:14<00:18, 24.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14823/15290 [08:14<00:18, 25.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14826/15290 [08:15<00:18, 25.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14829/15290 [08:15<00:18, 25.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14832/15290 [08:15<00:18, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14835/15290 [08:15<00:18, 25.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14838/15290 [08:15<00:17, 25.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14841/15290 [08:15<00:17, 25.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14844/15290 [08:15<00:17, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14847/15290 [08:15<00:17, 25.25it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14850/15290 [08:15<00:17, 25.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14853/15290 [08:16<00:17, 24.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14856/15290 [08:16<00:17, 25.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14859/15290 [08:16<00:17, 25.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14862/15290 [08:16<00:16, 25.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14865/15290 [08:16<00:16, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14868/15290 [08:16<00:16, 25.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14871/15290 [08:16<00:16, 25.66it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14874/15290 [08:16<00:16, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14877/15290 [08:17<00:16, 25.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14880/15290 [08:17<00:16, 25.53it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14883/15290 [08:17<00:15, 25.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14886/15290 [08:17<00:15, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14889/15290 [08:17<00:15, 26.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14892/15290 [08:17<00:15, 25.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14895/15290 [08:17<00:15, 25.63it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14898/15290 [08:17<00:15, 25.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14901/15290 [08:17<00:15, 25.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14904/15290 [08:18<00:15, 25.22it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
97%|█████████▋| 14907/15290 [08:18<00:15, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14910/15290 [08:18<00:14, 25.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14913/15290 [08:18<00:14, 25.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14916/15290 [08:18<00:14, 25.68it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14919/15290 [08:18<00:14, 26.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14922/15290 [08:18<00:14, 25.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14925/15290 [08:18<00:14, 25.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14928/15290 [08:19<00:14, 24.80it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14931/15290 [08:19<00:14, 25.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14934/15290 [08:19<00:14, 25.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14937/15290 [08:19<00:14, 24.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14940/15290 [08:19<00:13, 25.41it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14943/15290 [08:19<00:13, 25.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14946/15290 [08:19<00:13, 25.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14949/15290 [08:19<00:14, 23.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14952/15290 [08:20<00:15, 22.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14955/15290 [08:20<00:15, 22.09it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14958/15290 [08:20<00:14, 22.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14961/15290 [08:20<00:14, 22.28it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14964/15290 [08:20<00:14, 22.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14967/15290 [08:20<00:14, 22.52it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14970/15290 [08:20<00:14, 22.74it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14973/15290 [08:20<00:14, 22.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14976/15290 [08:21<00:14, 21.10it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14979/15290 [08:21<00:14, 21.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14982/15290 [08:21<00:14, 20.81it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14985/15290 [08:21<00:14, 21.44it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14988/15290 [08:21<00:14, 21.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14991/15290 [08:21<00:14, 20.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14994/15290 [08:21<00:13, 21.18it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 14997/15290 [08:22<00:14, 20.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15000/15290 [08:22<00:13, 21.02it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15003/15290 [08:22<00:13, 21.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15006/15290 [08:22<00:14, 19.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15008/15290 [08:22<00:14, 19.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15011/15290 [08:22<00:14, 19.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15014/15290 [08:22<00:13, 21.15it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15017/15290 [08:23<00:12, 21.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15020/15290 [08:23<00:12, 22.16it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15023/15290 [08:23<00:12, 22.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15026/15290 [08:23<00:11, 22.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15029/15290 [08:23<00:11, 22.86it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15032/15290 [08:23<00:10, 23.69it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15035/15290 [08:23<00:10, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15038/15290 [08:23<00:10, 24.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15041/15290 [08:24<00:10, 24.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15044/15290 [08:24<00:09, 24.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15047/15290 [08:24<00:09, 25.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15050/15290 [08:24<00:09, 25.38it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15053/15290 [08:24<00:09, 25.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15056/15290 [08:24<00:09, 24.76it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
98%|█████████▊| 15059/15290 [08:24<00:09, 24.23it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15062/15290 [08:24<00:09, 23.99it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15065/15290 [08:25<00:09, 23.60it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15068/15290 [08:25<00:09, 23.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15071/15290 [08:25<00:09, 23.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15074/15290 [08:25<00:09, 23.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15077/15290 [08:25<00:09, 23.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15080/15290 [08:25<00:09, 23.08it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15083/15290 [08:25<00:09, 22.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15086/15290 [08:25<00:08, 22.95it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15089/15290 [08:26<00:09, 22.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15092/15290 [08:26<00:08, 22.17it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15095/15290 [08:26<00:09, 21.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▊| 15098/15290 [08:26<00:08, 22.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15101/15290 [08:26<00:08, 22.51it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15104/15290 [08:26<00:08, 22.57it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15107/15290 [08:26<00:08, 22.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15110/15290 [08:27<00:07, 23.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15113/15290 [08:27<00:07, 23.30it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15116/15290 [08:27<00:07, 23.67it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15119/15290 [08:27<00:07, 23.32it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15122/15290 [08:27<00:07, 23.36it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15125/15290 [08:27<00:07, 23.06it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15128/15290 [08:27<00:07, 22.96it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15131/15290 [08:27<00:06, 23.65it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15134/15290 [08:28<00:06, 23.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15137/15290 [08:28<00:06, 23.62it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15140/15290 [08:28<00:06, 24.37it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15143/15290 [08:28<00:06, 24.14it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15146/15290 [08:28<00:06, 23.98it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15149/15290 [08:28<00:05, 24.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15152/15290 [08:28<00:05, 23.93it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15155/15290 [08:28<00:05, 23.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15158/15290 [08:29<00:05, 24.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15161/15290 [08:29<00:05, 23.84it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15164/15290 [08:29<00:05, 24.59it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15167/15290 [08:29<00:04, 24.78it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15170/15290 [08:29<00:04, 24.42it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15173/15290 [08:29<00:04, 24.35it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15176/15290 [08:29<00:04, 24.48it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15179/15290 [08:29<00:04, 24.39it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15182/15290 [08:30<00:04, 24.75it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15185/15290 [08:30<00:04, 24.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15188/15290 [08:30<00:04, 24.19it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15191/15290 [08:30<00:04, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15194/15290 [08:30<00:03, 24.82it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15197/15290 [08:30<00:03, 24.27it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15200/15290 [08:30<00:03, 24.55it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15203/15290 [08:30<00:03, 23.91it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15206/15290 [08:31<00:03, 23.77it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15209/15290 [08:31<00:03, 24.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
99%|█████████▉| 15212/15290 [08:31<00:03, 23.87it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15215/15290 [08:31<00:03, 24.20it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15218/15290 [08:31<00:02, 24.26it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15221/15290 [08:31<00:02, 24.01it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15224/15290 [08:31<00:02, 24.47it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15227/15290 [08:31<00:02, 24.33it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15230/15290 [08:32<00:02, 23.94it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15233/15290 [08:32<00:02, 24.49it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15236/15290 [08:32<00:02, 24.34it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15239/15290 [08:32<00:02, 24.24it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15242/15290 [08:32<00:01, 24.70it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15245/15290 [08:32<00:01, 24.07it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15248/15290 [08:32<00:01, 24.05it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15251/15290 [08:32<00:01, 24.21it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15254/15290 [08:33<00:01, 23.92it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15257/15290 [08:33<00:01, 23.88it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15260/15290 [08:33<00:01, 23.58it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15263/15290 [08:33<00:01, 23.54it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15266/15290 [08:33<00:01, 23.79it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15269/15290 [08:33<00:00, 23.29it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15272/15290 [08:33<00:00, 23.50it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15275/15290 [08:33<00:00, 23.43it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15278/15290 [08:34<00:00, 23.11it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15281/15290 [08:34<00:00, 22.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15284/15290 [08:34<00:00, 22.73it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|█████████▉| 15287/15290 [08:34<00:00, 23.31it/s]C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
C:\Users\kadab\AppData\Local\Temp\ipykernel_32196\279798859.py:11: PerformanceWarning: DataFrame is highly fragmented. This is usually the result of calling `frame.insert` many times, which has poor performance. Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`
df_nlp_score[master_key] = np.vectorize(create_score_column,otypes = [float])(df_nlp_score['dict'],master_key,df_nlp_score['word_count'],score_type,0,idf_all,idf_word)
100%|██████████| 15290/15290 [08:34<00:00, 29.71it/s]